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abs,"\nabs( x:ndarray|ArrayLikeObject|number[, options:Object] )\n Computes the absolute value.\n"
abs.assign,"\nabs.assign( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n Computes the absolute value and assigns results to a provided output array.\n"
acartesianPower,"\nacartesianPower( x:ArrayLikeObject, n:integer )\n Returns the Cartesian power.\n"
acartesianProduct,"\nacartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )\n Returns the Cartesian product.\n"
acartesianSquare,"\nacartesianSquare( x:ArrayLikeObject )\n Returns the Cartesian square.\n"
acronym,"\nacronym( str:string[, options:Object] )\n Generates an acronym for a given string.\n"
aempty,"\naempty( length:integer[, dtype:string] )\n Creates an uninitialized array having a specified length.\n"
aemptyLike,"\naemptyLike( x:TypedArray|Array[, dtype:string] )\n Creates an uninitialized array having the same length and data type as a\n provided input array.\n"
AFINN_96,"\nAFINN_96()\n Returns a list of English words rated for valence.\n"
AFINN_111,"\nAFINN_111()\n Returns a list of English words rated for valence.\n"
afull,"\nafull( length:integer, value:any[, dtype:string] )\n Returns a filled array having a specified length.\n"
afullLike,"\nafullLike( x:TypedArray|Array[, dtype:string] )\n Returns a filled array having the same length and data type as a provided\n input array.\n"
alias2pkg,"\nalias2pkg( alias:string )\n Returns the package name associated with a provided alias.\n"
alias2related,"\nalias2related( alias:string )\n Returns aliases related to a specified alias.\n"
alias2standalone,"\nalias2standalone( alias:string )\n Returns the standalone package name associated with a provided alias.\n"
aliases,"\naliases( [namespace:string] )\n Returns a list of standard library aliases.\n"
allocUnsafe,"\nallocUnsafe( size:integer )\n Allocates a buffer having a specified number of bytes.\n"
amskfilter,"\namskfilter( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n Returns a new array by applying a mask to a provided input array.\n"
amskput,"\namskput( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, \n options:Object] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n"
amskreject,"\namskreject( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n Returns a new array by applying a mask to a provided input array.\n"
anans,"\nanans( length:integer[, dtype:string] )\n Returns an array filled with NaNs and having a specified length.\n"
anansLike,"\nanansLike( x:TypedArray|Array[, dtype:string] )\n Returns an array filled with NaNs and having the same length and data type\n as a provided input array.\n"
anova1,"\nanova1( x:Array<number>, factor:Array[, options:Object] )\n Performs a one-way analysis of variance.\n"
ANSCOMBES_QUARTET,"\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n"
any,"\nany( collection:Array|TypedArray|Object )\n Tests whether at least one element in a collection is truthy.\n"
anyBy,"\nanyBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n"
anyByAsync,"\nanyByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n"
anyByAsync.factory,"\nanyByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n"
anyByRight,"\nanyByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n"
anyByRightAsync,"\nanyByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n"
anyByRightAsync.factory,"\nanyByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n"
anyInBy,"\nanyInBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one value in an object passes a test implemented by\n a predicate function.\n"
anyOwnBy,"\nanyOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one own property of an object passes a\n test implemented by a predicate function.\n"
aones,"\naones( length:integer[, dtype:string] )\n Returns an array filled with ones and having a specified length.\n"
aonesLike,"\naonesLike( x:TypedArray|Array[, dtype:string] )\n Returns an array filled with ones and having the same length and data type\n as a provided input array.\n"
aoneTo,"\naoneTo( n:integer[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n"
aoneToLike,"\naoneToLike( x:TypedArray|Array[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one and having the same length and data type as a provided\n input array.\n"
APERY,"\nAPERY\n Apéry's constant.\n"
aplace,"\naplace( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, \n options:Object] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n"
append,"\nappend( collection1:Array|TypedArray|Object, \n collection2:Array|TypedArray|Object )\n Adds the elements of one collection to the end of another collection.\n"
aput,"\naput( x:ArrayLikeObject, indices:ArrayLikeObject<integer>, \n values:ArrayLikeObject[, options:Object] )\n Replaces specified elements of an array with provided values.\n"
ARCH,"\nARCH\n Operating system CPU architecture for which the JavaScript runtime binary\n was compiled.\n"
argumentFunction,"\nargumentFunction( idx:integer )\n Returns a function which always returns a specified argument.\n"
ARGV,"\nARGV\n An array containing command-line arguments passed when launching the calling\n process.\n"
array,"\narray( [buffer:Array|TypedArray|Buffer|ndarray,] [options:Object] )\n Returns a multidimensional array.\n"
array2buffer,"\narray2buffer( arr:Array<integer> )\n Allocates a buffer using an octet array.\n"
array2fancy,"\narray2fancy( x:Array|TypedArray|Object[, options:Object] )\n Converts an array to an object supporting fancy indexing.\n"
array2fancy.factory,"\narray2fancy.factory( [options:Object] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n"
array2fancy.idx,"\narray2fancy.idx( x:Array|TypedArray|Object[, options:Object] )\n Wraps a provided array as an array index object.\n"
array2iterator,"\narray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of an array-like\n object.\n"
array2iteratorRight,"\narray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object.\n"
ArrayBuffer,"\nArrayBuffer( size:integer )\n Returns an array buffer having a specified number of bytes.\n"
ArrayBuffer.length,"\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n"
ArrayBuffer.isView,"\nArrayBuffer.isView( arr:any )\n Returns a boolean indicating if provided an array buffer view.\n"
ArrayBuffer.prototype.byteLength,"\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n"
ArrayBuffer.prototype.slice,"\nArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n Copies the bytes of an array buffer to a new array buffer.\n"
arraybuffer2buffer,"\narraybuffer2buffer( buf:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Allocates a buffer from an ArrayBuffer.\n"
arrayCtors,"\narrayCtors( dtype:string )\n Returns an array constructor.\n"
arrayDataType,"\narrayDataType( array:any )\n Returns the data type of an array.\n"
arrayDataTypes,"\narrayDataTypes( [kind:string] )\n Returns a list of array data types.\n"
ArrayIndex,"\nArrayIndex( x:Array|TypedArray|Object[, options:Object] )\n Wraps a provided array as an array index object.\n"
ArrayIndex.free,"\nArrayIndex.free( id:string )\n Frees the instance associated with a provided identifier.\n"
ArrayIndex.get,"\nArrayIndex.get( id:string )\n Returns the array associated with the instance having a provided identifier.\n"
ArrayIndex.prototype.data,"\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n"
ArrayIndex.prototype.dtype,"\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n"
ArrayIndex.prototype.id,"\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n"
ArrayIndex.prototype.isCached,"\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n"
ArrayIndex.prototype.type,"\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n"
ArrayIndex.prototype.toString,"\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n"
ArrayIndex.prototype.toJSON,"\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n"
arrayMinDataType,"\narrayMinDataType( value:any )\n Returns the minimum array data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n"
arrayMostlySafeCasts,"\narrayMostlySafeCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast and, for floating-point data types, can be downcast.\n"
arrayNextDataType,"\narrayNextDataType( [dtype:string] )\n Returns the next larger array data type of the same kind.\n"
arrayPromotionRules,"\narrayPromotionRules( [dtype1:any, dtype2:any] )\n Returns the array data type with the smallest size and closest \"kind\" to\n which array data types can be safely cast.\n"
arraySafeCasts,"\narraySafeCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast.\n"
arraySameKindCasts,"\narraySameKindCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast or cast within the same \"kind\".\n"
arrayShape,"\narrayShape( arr:ArrayLikeObject )\n Determines array dimensions.\n"
arrayStream,"\narrayStream( src:ArrayLikeObject[, options:Object] )\n Creates a readable stream from an array-like object.\n"
arrayStream.factory,"\narrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects.\n"
arrayStream.objectMode,"\narrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n Returns an \"objectMode\" readable stream from an array-like object.\n"
arrayview2iterator,"\narrayview2iterator( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of an array-like object\n view.\n"
arrayview2iteratorRight,"\narrayview2iteratorRight( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n"
aslice,"\naslice( x:ArrayLikeObject[, start:integer[, end:integer]] )\n Returns a shallow copy of a portion of an array.\n"
AsyncIteratorSymbol,"\nAsyncIteratorSymbol\n Async iterator symbol.\n"
atake,"\natake( x:Array|TypedArray|Object, indices:ArrayLikeObject<integer>[, \n options:Object] )\n Takes elements from an array.\n"
azeros,"\nazeros( length:integer[, dtype:string] )\n Returns a zero-filled array having a specified length.\n"
azerosLike,"\nazerosLike( x:TypedArray|Array[, dtype:string] )\n Returns a zero-filled array having the same length and data type as a\n provided input array.\n"
azeroTo,"\nazeroTo( n:integer[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n"
azeroToLike,"\nazeroToLike( x:TypedArray|Array[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero and having the same length and data type as a provided\n input array.\n"
bartlettTest,"\nbartlettTest( ...x:Array[, options:Object] )\n Computes Bartlett’s test for equal variances.\n"
base.abs,"\nbase.abs( x:number )\n Computes the absolute value of a double-precision floating-point number `x`.\n"
base.abs2,"\nbase.abs2( x:number )\n Computes the squared absolute value of a double-precision floating-point\n `x`.\n"
base.abs2f,"\nbase.abs2f( x:number )\n Computes the squared absolute value of a single-precision floating-point\n `x`.\n"
base.absdiff,"\nbase.absdiff( x:number, y:number )\n Computes the absolute difference.\n"
base.absf,"\nbase.absf( x:number )\n Computes the absolute value of a single-precision floating-point number `x`.\n"
base.acartesianPower,"\nbase.acartesianPower( x:ArrayLikeObject, n:integer )\n Returns the Cartesian power.\n"
base.acartesianProduct,"\nbase.acartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )\n Returns the Cartesian product.\n"
base.acartesianSquare,"\nbase.acartesianSquare( x:ArrayLikeObject )\n Returns the Cartesian square.\n"
base.acos,"\nbase.acos( x:number )\n Compute the arccosine of a double-precision floating-point number.\n"
base.acosd,"\nbase.acosd( x:number )\n Computes the arccosine (in degrees) of a double-precision floating-point \n number.\n"
base.acosf,"\nbase.acosf( x:number )\n Computes the arccosine of a single-precision floating-point number.\n"
base.acosh,"\nbase.acosh( x:number )\n Computes the hyperbolic arccosine of a double-precision floating-point\n number.\n"
base.acot,"\nbase.acot( x:number )\n Computes the inverse cotangent of a double-precision floating-point number.\n"
base.acotd,"\nbase.acotd( x:number )\n Computes the arccotangent (in degrees) of a double-precision floating-point\n number.\n"
base.acotf,"\nbase.acotf( x:number )\n Computes the inverse cotangent of a single-precision floating-point number.\n"
base.acoth,"\nbase.acoth( x:number )\n Computes the inverse hyperbolic cotangent of a double-precision floating-\n point number.\n"
base.acovercos,"\nbase.acovercos( x:number )\n Computes the inverse coversed cosine.\n"
base.acoversin,"\nbase.acoversin( x:number )\n Computes the inverse coversed sine.\n"
base.acsc,"\nbase.acsc( x:number )\n Computes the arccosecant of a number.\n"
base.acscd,"\nbase.acscd( x:number )\n Computes the arccosecant of (in degrees) a double-precision floating-point\n number.\n"
base.acscdf,"\nbase.acscdf( x:number )\n Computes the arccosecant (in degrees) of a single-precision floating-point\n number.\n"
base.acscf,"\nbase.acscf( x:number )\n Computes the arccosecant of a single-precision floating-point number.\n"
base.acsch,"\nbase.acsch( x:number )\n Computes the hyperbolic arccosecant of a number.\n"
base.add,"\nbase.add( x:number, y:number )\n Computes the sum of two double-precision floating-point numbers `x` and `y`.\n"
base.add3,"\nbase.add3( x:number, y:number, z:number )\n Computes the sum of three double-precision floating-point numbers.\n"
base.add4,"\nbase.add4( x:number, y:number, z:number, w:number )\n Computes the sum of four double-precision floating-point numbers.\n"
base.add5,"\nbase.add5( x:number, y:number, z:number, w:number, u:number )\n Computes the sum of five double-precision floating-point numbers.\n"
base.addf,"\nbase.addf( x:number, y:number )\n Computes the sum of two single-precision floating-point numbers `x` and `y`.\n"
base.afilled,"\nbase.afilled( value:any, len:integer )\n Returns a filled \"generic\" array.\n"
base.afilled2d,"\nbase.afilled2d( value:any, shape:Array<integer> )\n Returns a filled two-dimensional nested array.\n"
base.afilled2dBy,"\nbase.afilled2dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n Returns a filled two-dimensional nested array according to a provided\n callback function.\n"
base.afilled3d,"\nbase.afilled3d( value:any, shape:Array<integer> )\n Returns a filled three-dimensional nested array.\n"
base.afilled3dBy,"\nbase.afilled3dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n Returns a filled three-dimensional nested array according to a provided\n callback function.\n"
base.afilled4d,"\nbase.afilled4d( value:any, shape:Array<integer> )\n Returns a filled four-dimensional nested array.\n"
base.afilled4dBy,"\nbase.afilled4dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n Returns a filled four-dimensional nested array according to a provided\n callback function.\n"
base.afilled5d,"\nbase.afilled5d( value:any, shape:Array<integer> )\n Returns a filled five-dimensional nested array.\n"
base.afilled5dBy,"\nbase.afilled5dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n Returns a filled five-dimensional nested array according to a provided\n callback function.\n"
base.afilledBy,"\nbase.afilledBy( len:integer, clbk:Function[, thisArg:any] )\n Returns a filled \"generic\" array according to a provided callback function.\n"
base.afillednd,"\nbase.afillednd( value:any, shape:Array<integer> )\n Returns a filled n-dimensional nested array.\n"
base.afilledndBy,"\nbase.afilledndBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n Returns a filled n-dimensional nested array according to a callback\n function.\n"
base.afilter,"\nbase.afilter( x:Array|TypedArray|Object, predicate:Function[, thisArg:any] )\n Returns a shallow copy of an array containing only those elements which pass\n a test implemented by a predicate function.\n"
base.afirst,"\nbase.afirst( arr:ArrayLikeObject )\n Returns the first element of an array-like object.\n"
base.aflatten,"\nbase.aflatten( x:Array, shape:Array<integer>, colexicographic:boolean )\n Flattens an n-dimensional nested array.\n"
base.aflatten.assign,"\nbase.aflatten.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens an n-dimensional nested array and assigns elements to a provided\n output array.\n"
base.aflatten2d,"\nbase.aflatten2d( x:Array, shape:Array<integer>, colexicographic:boolean )\n Flattens a two-dimensional nested array.\n"
base.aflatten2d.assign,"\nbase.aflatten2d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a two-dimensional nested array and assigns elements to a provided\n output array.\n"
base.aflatten2dBy,"\nbase.aflatten2dBy( x:Array, shape:Array<integer>, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a two-dimensional nested array according to a callback function.\n"
base.aflatten2dBy.assign,"\nbase.aflatten2dBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a two-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n"
base.aflatten3d,"\nbase.aflatten3d( x:ArrayLikeObject, shape:Array<integer>, \n colexicographic:boolean )\n Flattens a three-dimensional nested array.\n"
base.aflatten3d.assign,"\nbase.aflatten3d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a three-dimensional nested array and assigns elements to a provided\n output array.\n"
base.aflatten3dBy,"\nbase.aflatten3dBy( x:ArrayLikeObject, shape:Array<integer>, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a three-dimensional nested array according to a callback function.\n"
base.aflatten3dBy.assign,"\nbase.aflatten3dBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a three-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n"
base.aflatten4d,"\nbase.aflatten4d( x:ArrayLikeObject, shape:Array<integer>, \n colexicographic:boolean )\n Flattens a four-dimensional nested array.\n"
base.aflatten4d.assign,"\nbase.aflatten4d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a four-dimensional nested array and assigns elements to a provided\n output array.\n"
base.aflatten4dBy,"\nbase.aflatten4dBy( x:ArrayLikeObject, shape:Array<integer>, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a four-dimensional nested array according to a callback function.\n"
base.aflatten4dBy.assign,"\nbase.aflatten4dBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a four-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n"
base.aflatten5d,"\nbase.aflatten5d( x:ArrayLikeObject, shape:Array<integer>, \n colexicographic:boolean )\n Flattens a five-dimensional nested array.\n"
base.aflatten5d.assign,"\nbase.aflatten5d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a five-dimensional nested array and assigns elements to a provided\n output array.\n"
base.aflatten5dBy,"\nbase.aflatten5dBy( x:ArrayLikeObject, shape:Array<integer>, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a five-dimensional nested array according to a callback function.\n"
base.aflatten5dBy.assign,"\nbase.aflatten5dBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a five-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n"
base.aflattenBy,"\nbase.aflattenBy( x:Array, shape:Array<integer>, colex:boolean, clbk:Function[, \n thisArg:any] )\n Flattens an n-dimensional nested array according to a callback function.\n"
base.aflattenBy.assign,"\nbase.aflattenBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens an n-dimensional nested array according to a callback function and\n assigns elements to a provided output array.\n"
base.afliplr2d,"\nbase.afliplr2d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a two-dimensional\n nested input array.\n"
base.afliplr3d,"\nbase.afliplr3d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a three-\n dimensional nested input array.\n"
base.afliplr4d,"\nbase.afliplr4d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a four-\n dimensional nested input array.\n"
base.afliplr5d,"\nbase.afliplr5d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a five-\n dimensional nested input array.\n"
base.aflipud2d,"\nbase.aflipud2d( x:ArrayLikeObject )\n Reverses the order of elements along the first dimension of a two-\n dimensional nested input array.\n"
base.aflipud3d,"\nbase.aflipud3d( x:ArrayLikeObject )\n Reverses the order of elements along the second-to-last dimension of a\n three-dimensional nested input array.\n"
base.aflipud4d,"\nbase.aflipud4d( x:ArrayLikeObject )\n Reverses the order of elements along the second-to-last dimension of a four-\n dimensional nested input array.\n"
base.aflipud5d,"\nbase.aflipud5d( x:ArrayLikeObject )\n Reverses the order of elements along the second-to-last dimension of a five-\n dimensional nested input array.\n"
base.ahavercos,"\nbase.ahavercos( x:number )\n Computes the inverse half-value versed cosine.\n"
base.ahaversin,"\nbase.ahaversin( x:number )\n Computes the inverse half-value versed sine.\n"
base.altcase,"\nbase.altcase( str:string )\n Converts a string to alternate case.\n"
base.aones,"\nbase.aones( len:integer )\n Returns a \"generic\" array filled with ones.\n"
base.aones2d,"\nbase.aones2d( shape:Array<integer> )\n Returns a two-dimensional nested array filled with ones.\n"
base.aones3d,"\nbase.aones3d( shape:Array<integer> )\n Returns a three-dimensional nested array filled with ones.\n"
base.aones4d,"\nbase.aones4d( shape:Array<integer> )\n Returns a four-dimensional nested array filled with ones.\n"
base.aones5d,"\nbase.aones5d( shape:Array<integer> )\n Returns a five-dimensional nested array filled with ones.\n"
base.aonesnd,"\nbase.aonesnd( shape:Array<integer> )\n Returns an n-dimensional nested array filled with ones.\n"
base.aoneTo,"\nbase.aoneTo( n:number )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n"
base.aoneTo.assign,"\nbase.aoneTo.assign( out:ArrayLikeObject, stride:integer, offset:integer )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from one.\n"
base.args2multislice,"\nbase.args2multislice( args:Array<Slice|integer|null|undefined> )\n Creates a MultiSlice object from a list of MultiSlice constructor arguments.\n"
base.asec,"\nbase.asec( x:number )\n Computes the inverse (arc) secant of a number.\n"
base.asecd,"\nbase.asecd( x:number )\n Computes the arcsecant (in degrees) of a double-precision floating-point\n number.\n"
base.asecdf,"\nbase.asecdf( x:number )\n Computes the arcsecant (in degrees) of a single-precision floating-point\n number.\n"
base.asecf,"\nbase.asecf( x:number )\n Computes the inverse (arc) secant of a single-precision\n floating-point number.\n"
base.asech,"\nbase.asech( x:number )\n Computes the hyperbolic arcsecant of a number.\n"
base.asin,"\nbase.asin( x:number )\n Computes the arcsine of a double-precision floating-point number.\n"
base.asind,"\nbase.asind( x:number )\n Computes the arcsine (in degrees) of a double-precision floating-point\n number.\n"
base.asindf,"\nbase.asindf( x:number )\n Computes the arcsine (in degrees) of a single-precision floating-point\n number.\n"
base.asinf,"\nbase.asinf( x:number )\n Computes the arcsine of a single-precision floating-point number.\n"
base.asinh,"\nbase.asinh( x:number )\n Computes the hyperbolic arcsine of a double-precision floating-point number.\n"
base.atan,"\nbase.atan( x:number )\n Computes the arctangent of a double-precision floating-point number.\n"
base.atan2,"\nbase.atan2( y:number, x:number )\n Computes the angle in the plane (in radians) between the positive x-axis and\n the ray from (0,0) to the point (x,y).\n"
base.atand,"\nbase.atand( x:number )\n Computes the arctangent (in degrees) of a double-precision floating-point\n number.\n"
base.atanf,"\nbase.atanf( x:number )\n Computes the arctangent of a single-precision floating-point number.\n"
base.atanh,"\nbase.atanh( x:number )\n Computes the hyperbolic arctangent of a double-precision floating-point\n number.\n"
base.avercos,"\nbase.avercos( x:number )\n Computes the inverse versed cosine.\n"
base.aversin,"\nbase.aversin( x:number )\n Computes the inverse versed sine.\n"
base.azeros,"\nbase.azeros( len:integer )\n Returns a zero-filled \"generic\" array.\n"
base.azeros2d,"\nbase.azeros2d( shape:Array<integer> )\n Returns a zero-filled two-dimensional nested array.\n"
base.azeros3d,"\nbase.azeros3d( shape:Array<integer> )\n Returns a zero-filled three-dimensional nested array.\n"
base.azeros4d,"\nbase.azeros4d( shape:Array<integer> )\n Returns a zero-filled four-dimensional nested array.\n"
base.azeros5d,"\nbase.azeros5d( shape:Array<integer> )\n Returns a zero-filled five-dimensional nested array.\n"
base.azerosnd,"\nbase.azerosnd( shape:Array<integer> )\n Returns a zero-filled n-dimensional nested array.\n"
base.azeroTo,"\nbase.azeroTo( n:number )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n"
base.azeroTo.assign,"\nbase.azeroTo.assign( out:ArrayLikeObject, stride:integer, offset:integer )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from zero.\n"
base.bernoulli,"\nbase.bernoulli( n:integer )\n Computes the nth Bernoulli number.\n"
base.besselj0,"\nbase.besselj0( x:number )\n Computes the Bessel function of the first kind of order zero.\n"
base.besselj1,"\nbase.besselj1( x:number )\n Computes the Bessel function of the first kind of order one.\n"
base.bessely0,"\nbase.bessely0( x:number )\n Computes the Bessel function of the second kind of order zero.\n"
base.bessely1,"\nbase.bessely1( x:number )\n Computes the Bessel function of the second kind of order one.\n"
base.beta,"\nbase.beta( x:number, y:number )\n Evaluates the beta function.\n"
base.betainc,"\nbase.betainc( x:number, a:number, b:number[, regularized:boolean[, \n upper:boolean]] )\n Computes the regularized incomplete beta function.\n"
base.betaincinv,"\nbase.betaincinv( p:number, a:number, b:number[, upper:boolean] )\n Computes the inverse of the lower incomplete beta function.\n"
base.betaln,"\nbase.betaln( a:number, b:number )\n Evaluates the natural logarithm of the beta function.\n"
base.binet,"\nbase.binet( x:number )\n Evaluates Binet's formula extended to real numbers.\n"
base.binomcoef,"\nbase.binomcoef( n:integer, k:integer )\n Computes the binomial coefficient of two integers.\n"
base.binomcoefln,"\nbase.binomcoefln( n:integer, k:integer )\n Computes the natural logarithm of the binomial coefficient of two integers.\n"
base.boxcox,"\nbase.boxcox( x:number, lambda:number )\n Computes a one-parameter Box-Cox transformation.\n"
base.boxcox1p,"\nbase.boxcox1p( x:number, lambda:number )\n Computes a one-parameter Box-Cox transformation of 1+x.\n"
base.boxcox1pinv,"\nbase.boxcox1pinv( y:number, lambda:number )\n Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n"
base.boxcoxinv,"\nbase.boxcoxinv( y:number, lambda:number )\n Computes the inverse of a one-parameter Box-Cox transformation.\n"
base.cabs,"\nbase.cabs( z:Complex128 )\n Computes the absolute value of a double-precision complex floating-point\n number.\n"
base.cabs2,"\nbase.cabs2( z:Complex128 )\n Computes the squared absolute value of a double-precision complex floating-\n point number.\n"
base.cabs2f,"\nbase.cabs2f( z:Complex64 )\n Computes the squared absolute value of a single-precision complex floating-\n point number.\n"
base.cabsf,"\nbase.cabsf( z:Complex64 )\n Computes the absolute value of a single-precision complex floating-point\n number.\n"
base.cadd,"\nbase.cadd( z1:Complex128, z2:Complex128 )\n Adds two double-precision complex floating-point numbers.\n"
base.cadd.assign,"\nbase.cadd.assign( re1:number, im1:number, re2:number, im2:number, \n out:ArrayLikeObject, strideOut:integer, offsetOut:integer )\n Adds two double-precision complex floating-point numbers and assigns results\n to a provided output array.\n"
base.cadd.strided,"\nbase.cadd.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, \n z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, \n so:integer, oo:integer )\n Adds two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n"
base.caddf,"\nbase.caddf( z1:Complex64, z2:Complex64 )\n Adds two single-precision complex floating-point numbers.\n"
base.camelcase,"\nbase.camelcase( str:string )\n Converts a string to camel case.\n"
base.capitalize,"\nbase.capitalize( str:string )\n Capitalizes the first character in a string.\n"
base.cbrt,"\nbase.cbrt( x:number )\n Computes the cube root of a double-precision floating-point number.\n"
base.cbrtf,"\nbase.cbrtf( x:number )\n Computes the cube root of a single-precision floating-point number.\n"
base.cceil,"\nbase.cceil( z:Complex128 )\n Rounds each component of a double-precision complex floating-point number\n toward positive infinity.\n"
base.cceilf,"\nbase.cceilf( z:Complex64 )\n Rounds a single-precision complex floating-point number toward positive\n infinity.\n"
base.cceiln,"\nbase.cceiln( z:Complex128, n:integer )\n Rounds each component of a double-precision complex number to the nearest\n multiple of `10^n` toward positive infinity.\n"
base.ccis,"\nbase.ccis( z:Complex128 )\n Evaluates the cis function for a double-precision complex floating-point\n number.\n"
base.cdiv,"\nbase.cdiv( z1:Complex128, z2:Complex128 )\n Divides two double-precision complex floating-point numbers.\n"
base.ceil,"\nbase.ceil( x:number )\n Rounds a double-precision floating-point number toward positive infinity.\n"
base.ceil2,"\nbase.ceil2( x:number )\n Rounds a numeric value to the nearest power of two toward positive infinity.\n"
base.ceil10,"\nbase.ceil10( x:number )\n Rounds a numeric value to the nearest power of ten toward positive infinity.\n"
base.ceilb,"\nbase.ceilb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward positive\n infinity.\n"
base.ceilf,"\nbase.ceilf( x:number )\n Rounds a single-precision floating-point number toward positive infinity.\n"
base.ceiln,"\nbase.ceiln( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n` toward positive\n infinity.\n"
base.ceilsd,"\nbase.ceilsd( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest number toward positive infinity with\n `n` significant figures.\n"
base.cexp,"\nbase.cexp( z:Complex128 )\n Evaluates the exponential function for a double-precision complex floating-\n point number.\n"
base.cflipsign,"\nbase.cflipsign( z:Complex128, y:number )\n Returns a double-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n"
base.cflipsignf,"\nbase.cflipsignf( z:Complex64, y:number )\n Returns a single-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n"
base.cfloor,"\nbase.cfloor( z:Complex128 )\n Rounds a double-precision complex floating-point number toward negative\n infinity.\n"
base.cfloorn,"\nbase.cfloorn( z:Complex128, n:integer )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n` toward negative infinity.\n"
base.cidentity,"\nbase.cidentity( z:Complex128 )\n Evaluates the identity function for a double-precision complex floating-\n point number.\n"
base.cidentityf,"\nbase.cidentityf( z:Complex64 )\n Evaluates the identity function for a single-precision complex floating-\n point number.\n"
base.cinv,"\nbase.cinv( z:Complex128 )\n Computes the inverse of a double-precision complex floating-point number.\n"
base.clamp,"\nbase.clamp( v:number, min:number, max:number )\n Restricts a double-precision floating-point number to a specified range.\n"
base.clampf,"\nbase.clampf( v:number, min:number, max:number )\n Restricts a single-precision floating-point number to a specified range.\n"
base.cmul,"\nbase.cmul( z1:Complex128, z2:Complex128 )\n Multiplies two double-precision complex floating-point numbers.\n"
base.cmul.assign,"\nbase.cmul.assign( re1:number, im1:number, re2:number, im2:number, \n out:ArrayLikeObject, strideOut:integer, offsetOut:integer )\n Multiplies two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n"
base.cmul.strided,"\nbase.cmul.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, \n z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, \n so:integer, oo:integer )\n Multiplies two double-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n"
base.cmulf,"\nbase.cmulf( z1:Complex64, z2:Complex64 )\n Multiplies two single-precision complex floating-point numbers.\n"
base.cneg,"\nbase.cneg( z )\n Negates a double-precision complex floating-point number.\n"
base.cnegf,"\nbase.cnegf( z )\n Negates a single-precision complex floating-point number.\n"
base.codePointAt,"\nbase.codePointAt( str:string, idx:integer, backward:boolean )\n Returns a Unicode code point from a string at a specified position.\n"
base.constantcase,"\nbase.constantcase( str:string )\n Converts a string to constant case.\n"
base.continuedFraction,"\nbase.continuedFraction( generator:Function[, options:Object] )\n Evaluates the continued fraction approximation for the supplied series\n generator using the modified Lentz algorithm.\n"
base.copysign,"\nbase.copysign( x:number, y:number )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n"
base.copysignf,"\nbase.copysignf( x:number, y:number )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n"
base.cos,"\nbase.cos( x:number )\n Computes the cosine of a number.\n"
base.cosd,"\nbase.cosd( x:number )\n Computes the cosine of an angle measured in degrees.\n"
base.cosh,"\nbase.cosh( x:number )\n Computes the hyperbolic cosine of a double-precision floating-point number.\n"
base.cosm1,"\nbase.cosm1( x:number )\n Computes the cosine of a number minus one.\n"
base.cospi,"\nbase.cospi( x:number )\n Computes the value of `cos(πx)`.\n"
base.cot,"\nbase.cot( x:number )\n Computes the cotangent of a number.\n"
base.cotd,"\nbase.cotd( x:number )\n Computes the cotangent of an angle measured in degrees.\n"
base.coth,"\nbase.coth( x:number )\n Computes the hyperbolic cotangent of a number.\n"
base.covercos,"\nbase.covercos( x:number )\n Computes the coversed cosine.\n"
base.coversin,"\nbase.coversin( x:number )\n Computes the coversed sine.\n"
base.cphase,"\nbase.cphase( z:Complex128 )\n Computes the argument of a double-precision complex floating-point number\n in radians.\n"
base.cpolar,"\nbase.cpolar( z:Complex128 )\n Returns the absolute value and phase of a double-precision complex\n floating-point number.\n"
base.cpolar.assign,"\nbase.cpolar.assign( z:Complex128, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n"
base.cround,"\nbase.cround( z:Complex128 )\n Rounds each component of a double-precision complex floating-point number\n to the nearest integer.\n"
base.croundn,"\nbase.croundn( z:Complex128, n:integer )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n`.\n"
base.csc,"\nbase.csc( x:number )\n Computes the cosecant of a number.\n"
base.cscd,"\nbase.cscd( x:number )\n Computes the cosecant of a degree.\n"
base.csch,"\nbase.csch( x:number )\n Computes the hyperbolic cosecant of a number.\n"
base.csignum,"\nbase.csignum( z:Complex128 )\n Evaluates the signum function of a double-precision complex floating-point\n number.\n"
base.csub,"\nbase.csub( z1:Complex128, z2:Complex128 )\n Subtracts two double-precision complex floating-point numbers.\n"
base.csubf,"\nbase.csubf( z1:Complex64, z2:Complex64 )\n Subtracts two single-precision complex floating-point numbers.\n"
base.deg2rad,"\nbase.deg2rad( x:number )\n Converts an angle from degrees to radians.\n"
base.deg2radf,"\nbase.deg2radf( x:number )\n Converts an angle from degrees to radians (single-precision).\n"
base.digamma,"\nbase.digamma( x:number )\n Evaluates the digamma function.\n"
base.diracDelta,"\nbase.diracDelta( x:number )\n Evaluates the Dirac delta function.\n"
base.div,"\nbase.div( x:number, y:number )\n Divides two double-precision floating-point numbers `x` and `y`.\n"
base.divf,"\nbase.divf( x:number, y:number )\n Divides two single-precision floating-point numbers `x` and `y`.\n"
base.dotcase,"\nbase.dotcase( str:string )\n Converts a string to dot case.\n"
base.dists.arcsine.Arcsine,"\nbase.dists.arcsine.Arcsine( [a:number, b:number] )\n Returns an arcsine distribution object.\n"
base.dists.arcsine.cdf,"\nbase.dists.arcsine.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for an arcsine\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n"
base.dists.arcsine.cdf.factory,"\nbase.dists.arcsine.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n"
base.dists.arcsine.entropy,"\nbase.dists.arcsine.entropy( a:number, b:number )\n Returns the differential entropy of an arcsine distribution (in nats).\n"
base.dists.arcsine.kurtosis,"\nbase.dists.arcsine.kurtosis( a:number, b:number )\n Returns the excess kurtosis of an arcsine distribution.\n"
base.dists.arcsine.logcdf,"\nbase.dists.arcsine.logcdf( x:number, a:number, b:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n"
base.dists.arcsine.logcdf.factory,"\nbase.dists.arcsine.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n"
base.dists.arcsine.logpdf,"\nbase.dists.arcsine.logpdf( x:number, a:number, b:number )\n Evaluates the logarithm of the probability density function (PDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n"
base.dists.arcsine.logpdf.factory,"\nbase.dists.arcsine.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n"
base.dists.arcsine.mean,"\nbase.dists.arcsine.mean( a:number, b:number )\n Returns the expected value of an arcsine distribution.\n"
base.dists.arcsine.median,"\nbase.dists.arcsine.median( a:number, b:number )\n Returns the median of an arcsine distribution.\n"
base.dists.arcsine.mode,"\nbase.dists.arcsine.mode( a:number, b:number )\n Returns the mode of an arcsine distribution.\n"
base.dists.arcsine.pdf,"\nbase.dists.arcsine.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for an arcsine distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n"
base.dists.arcsine.pdf.factory,"\nbase.dists.arcsine.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n"
base.dists.arcsine.quantile,"\nbase.dists.arcsine.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for an arcsine distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n"
base.dists.arcsine.quantile.factory,"\nbase.dists.arcsine.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n"
base.dists.arcsine.skewness,"\nbase.dists.arcsine.skewness( a:number, b:number )\n Returns the skewness of an arcsine distribution.\n"
base.dists.arcsine.stdev,"\nbase.dists.arcsine.stdev( a:number, b:number )\n Returns the standard deviation of an arcsine distribution.\n"
base.dists.arcsine.variance,"\nbase.dists.arcsine.variance( a:number, b:number )\n Returns the variance of an arcsine distribution.\n"
base.dists.bernoulli.Bernoulli,"\nbase.dists.bernoulli.Bernoulli( [p:number] )\n Returns a Bernoulli distribution object.\n"
base.dists.bernoulli.cdf,"\nbase.dists.bernoulli.cdf( x:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a Bernoulli\n distribution with success probability `p` at a value `x`.\n"
base.dists.bernoulli.cdf.factory,"\nbase.dists.bernoulli.cdf.factory( p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n"
base.dists.bernoulli.entropy,"\nbase.dists.bernoulli.entropy( p:number )\n Returns the entropy of a Bernoulli distribution with success probability\n `p` (in nats).\n"
base.dists.bernoulli.kurtosis,"\nbase.dists.bernoulli.kurtosis( p:number )\n Returns the excess kurtosis of a Bernoulli distribution with success\n probability `p`.\n"
base.dists.bernoulli.mean,"\nbase.dists.bernoulli.mean( p:number )\n Returns the expected value of a Bernoulli distribution with success\n probability `p`.\n"
base.dists.bernoulli.median,"\nbase.dists.bernoulli.median( p:number )\n Returns the median of a Bernoulli distribution with success probability `p`.\n"
base.dists.bernoulli.mgf,"\nbase.dists.bernoulli.mgf( t:number, p:number )\n Evaluates the moment-generating function (MGF) for a Bernoulli\n distribution with success probability `p` at a value `t`.\n"
base.dists.bernoulli.mgf.factory,"\nbase.dists.bernoulli.mgf.factory( p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n"
base.dists.bernoulli.mode,"\nbase.dists.bernoulli.mode( p:number )\n Returns the mode of a Bernoulli distribution with success probability `p`.\n"
base.dists.bernoulli.pmf,"\nbase.dists.bernoulli.pmf( x:number, p:number )\n Evaluates the probability mass function (PMF) for a Bernoulli distribution\n with success probability `p` at a value `x`.\n"
base.dists.bernoulli.pmf.factory,"\nbase.dists.bernoulli.pmf.factory( p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n"
base.dists.bernoulli.quantile,"\nbase.dists.bernoulli.quantile( r:number, p:number )\n Evaluates the quantile function for a Bernoulli distribution with success\n probability `p` at a probability `r`.\n"
base.dists.bernoulli.quantile.factory,"\nbase.dists.bernoulli.quantile.factory( p:number )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n"
base.dists.bernoulli.skewness,"\nbase.dists.bernoulli.skewness( p:number )\n Returns the skewness of a Bernoulli distribution with success probability\n `p`.\n"
base.dists.bernoulli.stdev,"\nbase.dists.bernoulli.stdev( p:number )\n Returns the standard deviation of a Bernoulli distribution with success\n probability `p`.\n"
base.dists.bernoulli.variance,"\nbase.dists.bernoulli.variance( p:number )\n Returns the variance of a Bernoulli distribution with success probability\n `p`.\n"
base.dists.beta.Beta,"\nbase.dists.beta.Beta( [α:number, β:number] )\n Returns a beta distribution object.\n"
base.dists.beta.cdf,"\nbase.dists.beta.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n"
base.dists.beta.cdf.factory,"\nbase.dists.beta.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n"
base.dists.beta.entropy,"\nbase.dists.beta.entropy( α:number, β:number )\n Returns the differential entropy of a beta distribution.\n"
base.dists.beta.kurtosis,"\nbase.dists.beta.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a beta distribution.\n"
base.dists.beta.logcdf,"\nbase.dists.beta.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n"
base.dists.beta.logcdf.factory,"\nbase.dists.beta.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n"
base.dists.beta.logpdf,"\nbase.dists.beta.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta distribution with first shape parameter `α` and second shape\n parameter `β` at a value `x`.\n"
base.dists.beta.logpdf.factory,"\nbase.dists.beta.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n"
base.dists.beta.mean,"\nbase.dists.beta.mean( α:number, β:number )\n Returns the expected value of a beta distribution.\n"
base.dists.beta.median,"\nbase.dists.beta.median( α:number, β:number )\n Returns the median of a beta distribution.\n"
base.dists.beta.mgf,"\nbase.dists.beta.mgf( t:number, α:number, β:number )\n Evaluates the moment-generating function (MGF) for a beta distribution with\n first shape parameter `α` and second shape parameter `β` at a value `t`.\n"
base.dists.beta.mgf.factory,"\nbase.dists.beta.mgf.factory( α:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n"
base.dists.beta.mode,"\nbase.dists.beta.mode( α:number, β:number )\n Returns the mode of a beta distribution.\n"
base.dists.beta.pdf,"\nbase.dists.beta.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n"
base.dists.beta.pdf.factory,"\nbase.dists.beta.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n"
base.dists.beta.quantile,"\nbase.dists.beta.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a beta distribution with first shape\n parameter `α` and second shape parameter `β` at a probability `p`.\n"
base.dists.beta.quantile.factory,"\nbase.dists.beta.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n"
base.dists.beta.skewness,"\nbase.dists.beta.skewness( α:number, β:number )\n Returns the skewness of a beta distribution.\n"
base.dists.beta.stdev,"\nbase.dists.beta.stdev( α:number, β:number )\n Returns the standard deviation of a beta distribution.\n"
base.dists.beta.variance,"\nbase.dists.beta.variance( α:number, β:number )\n Returns the variance of a beta distribution.\n"
base.dists.betaprime.BetaPrime,"\nbase.dists.betaprime.BetaPrime( [α:number, β:number] )\n Returns a beta prime distribution object.\n"
base.dists.betaprime.cdf,"\nbase.dists.betaprime.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n"
base.dists.betaprime.cdf.factory,"\nbase.dists.betaprime.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n"
base.dists.betaprime.kurtosis,"\nbase.dists.betaprime.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a beta prime distribution.\n"
base.dists.betaprime.logcdf,"\nbase.dists.betaprime.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta prime distribution with first shape parameter `α` and\n second shape parameter `β` at a value `x`.\n"
base.dists.betaprime.logcdf.factory,"\nbase.dists.betaprime.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n"
base.dists.betaprime.logpdf,"\nbase.dists.betaprime.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta prime distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n"
base.dists.betaprime.logpdf.factory,"\nbase.dists.betaprime.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n"
base.dists.betaprime.mean,"\nbase.dists.betaprime.mean( α:number, β:number )\n Returns the expected value of a beta prime distribution.\n"
base.dists.betaprime.mode,"\nbase.dists.betaprime.mode( α:number, β:number )\n Returns the mode of a beta prime distribution.\n"
base.dists.betaprime.pdf,"\nbase.dists.betaprime.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n"
base.dists.betaprime.pdf.factory,"\nbase.dists.betaprime.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n"
base.dists.betaprime.quantile,"\nbase.dists.betaprime.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a beta prime distribution with first\n shape parameter `α` and second shape parameter `β` at a probability `p`.\n"
base.dists.betaprime.quantile.factory,"\nbase.dists.betaprime.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n"
base.dists.betaprime.skewness,"\nbase.dists.betaprime.skewness( α:number, β:number )\n Returns the skewness of a beta prime distribution.\n"
base.dists.betaprime.stdev,"\nbase.dists.betaprime.stdev( α:number, β:number )\n Returns the standard deviation of a beta prime distribution.\n"
base.dists.betaprime.variance,"\nbase.dists.betaprime.variance( α:number, β:number )\n Returns the variance of a beta prime distribution.\n"
base.dists.binomial.Binomial,"\nbase.dists.binomial.Binomial( [n:integer, p:number] )\n Returns a binomial distribution object.\n"
base.dists.binomial.cdf,"\nbase.dists.binomial.cdf( x:number, n:integer, p:number )\n Evaluates the cumulative distribution function (CDF) for a binomial\n distribution with number of trials `n` and success probability `p` at a\n value `x`.\n"
base.dists.binomial.cdf.factory,"\nbase.dists.binomial.cdf.factory( n:integer, p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n"
base.dists.binomial.entropy,"\nbase.dists.binomial.entropy( n:integer, p:number )\n Returns the entropy of a binomial distribution.\n"
base.dists.binomial.kurtosis,"\nbase.dists.binomial.kurtosis( n:integer, p:number )\n Returns the excess kurtosis of a binomial distribution.\n"
base.dists.binomial.logpmf,"\nbase.dists.binomial.logpmf( x:number, n:integer, p:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n binomial distribution with number of trials `n` and success probability `p`\n at a value `x`.\n"
base.dists.binomial.logpmf.factory,"\nbase.dists.binomial.logpmf.factory( n:integer, p:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n"
base.dists.binomial.mean,"\nbase.dists.binomial.mean( n:integer, p:number )\n Returns the expected value of a binomial distribution.\n"
base.dists.binomial.median,"\nbase.dists.binomial.median( n:integer, p:number )\n Returns the median of a binomial distribution.\n"
base.dists.binomial.mgf,"\nbase.dists.binomial.mgf( t:number, n:integer, p:number )\n Evaluates the moment-generating function (MGF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `t`.\n"
base.dists.binomial.mgf.factory,"\nbase.dists.binomial.mgf.factory( n:integer, p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n"
base.dists.binomial.mode,"\nbase.dists.binomial.mode( n:integer, p:number )\n Returns the mode of a binomial distribution.\n"
base.dists.binomial.pmf,"\nbase.dists.binomial.pmf( x:number, n:integer, p:number )\n Evaluates the probability mass function (PMF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `x`.\n"
base.dists.binomial.pmf.factory,"\nbase.dists.binomial.pmf.factory( n:integer, p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n"
base.dists.binomial.quantile,"\nbase.dists.binomial.quantile( r:number, n:integer, p:number )\n Evaluates the quantile function for a binomial distribution with number of\n trials `n` and success probability `p` at a probability `r`.\n"
base.dists.binomial.quantile.factory,"\nbase.dists.binomial.quantile.factory( n:integer, p:number )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n"
base.dists.binomial.skewness,"\nbase.dists.binomial.skewness( n:integer, p:number )\n Returns the skewness of a binomial distribution.\n"
base.dists.binomial.stdev,"\nbase.dists.binomial.stdev( n:integer, p:number )\n Returns the standard deviation of a binomial distribution.\n"
base.dists.binomial.variance,"\nbase.dists.binomial.variance( n:integer, p:number )\n Returns the variance of a binomial distribution.\n"
base.dists.cauchy.Cauchy,"\nbase.dists.cauchy.Cauchy( [x0:number, Ɣ:number] )\n Returns a Cauchy distribution object.\n"
base.dists.cauchy.cdf,"\nbase.dists.cauchy.cdf( x:number, x0:number, Ɣ:number )\n Evaluates the cumulative distribution function (CDF) for a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n `x`.\n"
base.dists.cauchy.cdf.factory,"\nbase.dists.cauchy.cdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n"
base.dists.cauchy.entropy,"\nbase.dists.cauchy.entropy( x0:number, Ɣ:number )\n Returns the differential entropy of a Cauchy distribution (in nats).\n"
base.dists.cauchy.logcdf,"\nbase.dists.cauchy.logcdf( x:number, x0:number, Ɣ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n parameter `Ɣ` at a value `x`.\n"
base.dists.cauchy.logcdf.factory,"\nbase.dists.cauchy.logcdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n"
base.dists.cauchy.logpdf,"\nbase.dists.cauchy.logpdf( x:number, x0:number, Ɣ:number )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ` at a value `x`.\n"
base.dists.cauchy.logpdf.factory,"\nbase.dists.cauchy.logpdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n"
base.dists.cauchy.median,"\nbase.dists.cauchy.median( x0:number, Ɣ:number )\n Returns the median of a Cauchy distribution.\n"
base.dists.cauchy.mode,"\nbase.dists.cauchy.mode( x0:number, Ɣ:number )\n Returns the mode of a Cauchy distribution.\n"
base.dists.cauchy.pdf,"\nbase.dists.cauchy.pdf( x:number, x0:number, Ɣ:number )\n Evaluates the probability density function (PDF) for a Cauchy distribution\n with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n"
base.dists.cauchy.pdf.factory,"\nbase.dists.cauchy.pdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n"
base.dists.cauchy.quantile,"\nbase.dists.cauchy.quantile( p:number, x0:number, Ɣ:number )\n Evaluates the quantile function for a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ` at a probability `p`.\n"
base.dists.cauchy.quantile.factory,"\nbase.dists.cauchy.quantile.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n"
base.dists.chi.cdf,"\nbase.dists.chi.cdf( x:number, k:number )\n Evaluates the cumulative distribution function (CDF) for a chi distribution\n with degrees of freedom `k` at a value `x`.\n"
base.dists.chi.cdf.factory,"\nbase.dists.chi.cdf.factory( k:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n"
base.dists.chi.Chi,"\nbase.dists.chi.Chi( [k:number] )\n Returns a chi distribution object.\n"
base.dists.chi.entropy,"\nbase.dists.chi.entropy( k:number )\n Returns the differential entropy of a chi distribution (in nats).\n"
base.dists.chi.kurtosis,"\nbase.dists.chi.kurtosis( k:number )\n Returns the excess kurtosis of a chi distribution.\n"
base.dists.chi.logpdf,"\nbase.dists.chi.logpdf( x:number, k:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi distribution with degrees of freedom `k` at a value `x`.\n"
base.dists.chi.logpdf.factory,"\nbase.dists.chi.logpdf.factory( k:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n"
base.dists.chi.mean,"\nbase.dists.chi.mean( k:number )\n Returns the expected value of a chi distribution.\n"
base.dists.chi.mode,"\nbase.dists.chi.mode( k:number )\n Returns the mode of a chi distribution.\n"
base.dists.chi.pdf,"\nbase.dists.chi.pdf( x:number, k:number )\n Evaluates the probability density function (PDF) for a chi distribution with\n degrees of freedom `k` at a value `x`.\n"
base.dists.chi.pdf.factory,"\nbase.dists.chi.pdf.factory( k:number )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n"
base.dists.chi.quantile,"\nbase.dists.chi.quantile( p:number, k:number )\n Evaluates the quantile function for a chi distribution with degrees of\n freedom `k` at a probability `p`.\n"
base.dists.chi.quantile.factory,"\nbase.dists.chi.quantile.factory( k:number )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n"
base.dists.chi.skewness,"\nbase.dists.chi.skewness( k:number )\n Returns the skewness of a chi distribution.\n"
base.dists.chi.stdev,"\nbase.dists.chi.stdev( k:number )\n Returns the standard deviation of a chi distribution.\n"
base.dists.chi.variance,"\nbase.dists.chi.variance( k:number )\n Returns the variance of a chi distribution.\n"
base.dists.chisquare.cdf,"\nbase.dists.chisquare.cdf( x:number, k:number )\n Evaluates the cumulative distribution function (CDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n"
base.dists.chisquare.cdf.factory,"\nbase.dists.chisquare.cdf.factory( k:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n"
base.dists.chisquare.ChiSquare,"\nbase.dists.chisquare.ChiSquare( [k:number] )\n Returns a chi-squared distribution object.\n"
base.dists.chisquare.entropy,"\nbase.dists.chisquare.entropy( k:number )\n Returns the differential entropy of a chi-squared distribution (in nats).\n"
base.dists.chisquare.kurtosis,"\nbase.dists.chisquare.kurtosis( k:number )\n Returns the excess kurtosis of a chi-squared distribution.\n"
base.dists.chisquare.logpdf,"\nbase.dists.chisquare.logpdf( x:number, k:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n"
base.dists.chisquare.logpdf.factory,"\nbase.dists.chisquare.logpdf.factory( k:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n"
base.dists.chisquare.mean,"\nbase.dists.chisquare.mean( k:number )\n Returns the expected value of a chi-squared distribution.\n"
base.dists.chisquare.median,"\nbase.dists.chisquare.median( k:number )\n Returns the median of a chi-squared distribution.\n"
base.dists.chisquare.mgf,"\nbase.dists.chisquare.mgf( t:number, k:number )\n Evaluates the moment-generating function (MGF) for a chi-squared\n distribution with degrees of freedom `k` at a value `t`.\n"
base.dists.chisquare.mgf.factory,"\nbase.dists.chisquare.mgf.factory( k:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n"
base.dists.chisquare.mode,"\nbase.dists.chisquare.mode( k:number )\n Returns the mode of a chi-squared distribution.\n"
base.dists.chisquare.pdf,"\nbase.dists.chisquare.pdf( x:number, k:number )\n Evaluates the probability density function (PDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n"
base.dists.chisquare.pdf.factory,"\nbase.dists.chisquare.pdf.factory( k:number )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n"
base.dists.chisquare.quantile,"\nbase.dists.chisquare.quantile( p:number, k:number )\n Evaluates the quantile function for a chi-squared distribution with degrees\n of freedom `k` at a probability `p`.\n"
base.dists.chisquare.quantile.factory,"\nbase.dists.chisquare.quantile.factory( k:number )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n"
base.dists.chisquare.skewness,"\nbase.dists.chisquare.skewness( k:number )\n Returns the skewness of a chi-squared distribution.\n"
base.dists.chisquare.stdev,"\nbase.dists.chisquare.stdev( k:number )\n Returns the standard deviation of a chi-squared distribution.\n"
base.dists.chisquare.variance,"\nbase.dists.chisquare.variance( k:number )\n Returns the variance of a chi-squared distribution.\n"
base.dists.cosine.cdf,"\nbase.dists.cosine.cdf( x:number, μ:number, s:number )\n Evaluates the cumulative distribution function (CDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n"
base.dists.cosine.cdf.factory,"\nbase.dists.cosine.cdf.factory( μ:number, s:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n"
base.dists.cosine.Cosine,"\nbase.dists.cosine.Cosine( [μ:number, s:number] )\n Returns a raised cosine distribution object.\n"
base.dists.cosine.kurtosis,"\nbase.dists.cosine.kurtosis( μ:number, s:number )\n Returns the excess kurtosis of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n"
base.dists.cosine.logcdf,"\nbase.dists.cosine.logcdf( x:number, μ:number, s:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n"
base.dists.cosine.logcdf.factory,"\nbase.dists.cosine.logcdf.factory( μ:number, s:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n"
base.dists.cosine.logpdf,"\nbase.dists.cosine.logpdf( x:number, μ:number, s:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s` at a value `x`.\n"
base.dists.cosine.logpdf.factory,"\nbase.dists.cosine.logpdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n"
base.dists.cosine.mean,"\nbase.dists.cosine.mean( μ:number, s:number )\n Returns the expected value of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n"
base.dists.cosine.median,"\nbase.dists.cosine.median( μ:number, s:number )\n Returns the median of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n"
base.dists.cosine.mgf,"\nbase.dists.cosine.mgf( t:number, μ:number, s:number )\n Evaluates the moment-generating function (MGF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `t`.\n"
base.dists.cosine.mgf.factory,"\nbase.dists.cosine.mgf.factory( μ:number, s:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n"
base.dists.cosine.mode,"\nbase.dists.cosine.mode( μ:number, s:number )\n Returns the mode of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n"
base.dists.cosine.pdf,"\nbase.dists.cosine.pdf( x:number, μ:number, s:number )\n Evaluates the probability density function (PDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n"
base.dists.cosine.pdf.factory,"\nbase.dists.cosine.pdf.factory( μ:number, s:number )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n"
base.dists.cosine.quantile,"\nbase.dists.cosine.quantile( p:number, μ:number, s:number )\n Evaluates the quantile function for a raised cosine distribution with\n location parameter `μ` and scale parameter `s` at a probability `p`.\n"
base.dists.cosine.quantile.factory,"\nbase.dists.cosine.quantile.factory( μ:number, s:number )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n"
base.dists.cosine.skewness,"\nbase.dists.cosine.skewness( μ:number, s:number )\n Returns the skewness of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n"
base.dists.cosine.stdev,"\nbase.dists.cosine.stdev( μ:number, s:number )\n Returns the standard deviation of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n"
base.dists.cosine.variance,"\nbase.dists.cosine.variance( μ:number, s:number )\n Returns the variance of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n"
base.dists.degenerate.cdf,"\nbase.dists.degenerate.cdf( x:number, μ:number )\n Evaluates the cumulative distribution function (CDF) for a degenerate\n distribution with mean value `μ`.\n"
base.dists.degenerate.cdf.factory,"\nbase.dists.degenerate.cdf.factory( μ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n"
base.dists.degenerate.Degenerate,"\nbase.dists.degenerate.Degenerate( [μ:number] )\n Returns a degenerate distribution object.\n"
base.dists.degenerate.entropy,"\nbase.dists.degenerate.entropy( μ:number )\n Returns the entropy of a degenerate distribution with constant value `μ`.\n"
base.dists.degenerate.logcdf,"\nbase.dists.degenerate.logcdf( x:number, μ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a degenerate distribution with mean `μ`.\n"
base.dists.degenerate.logcdf.factory,"\nbase.dists.degenerate.logcdf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n"
base.dists.degenerate.logpdf,"\nbase.dists.degenerate.logpdf( x:number, μ:number )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a degenerate distribution with mean `μ`.\n"
base.dists.degenerate.logpdf.factory,"\nbase.dists.degenerate.logpdf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n"
base.dists.degenerate.logpmf,"\nbase.dists.degenerate.logpmf( x:number, μ:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n degenerate distribution with mean `μ`.\n"
base.dists.degenerate.logpmf.factory,"\nbase.dists.degenerate.logpmf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n"
base.dists.degenerate.mean,"\nbase.dists.degenerate.mean( μ:number )\n Returns the expected value of a degenerate distribution with constant value\n `μ`.\n"
base.dists.degenerate.median,"\nbase.dists.degenerate.median( μ:number )\n Returns the median of a degenerate distribution with constant value `μ`.\n"
base.dists.degenerate.mgf,"\nbase.dists.degenerate.mgf( x:number, μ:number )\n Evaluates the moment-generating function (MGF) for a degenerate distribution\n with mean `μ`.\n"
base.dists.degenerate.mgf.factory,"\nbase.dists.degenerate.mgf.factory( μ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n"
base.dists.degenerate.mode,"\nbase.dists.degenerate.mode( μ:number )\n Returns the mode of a degenerate distribution with constant value `μ`.\n"
base.dists.degenerate.pdf,"\nbase.dists.degenerate.pdf( x:number, μ:number )\n Evaluates the probability density function (PDF) for a degenerate\n distribution with mean `μ`.\n"
base.dists.degenerate.pdf.factory,"\nbase.dists.degenerate.pdf.factory( μ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n"
base.dists.degenerate.pmf,"\nbase.dists.degenerate.pmf( x:number, μ:number )\n Evaluates the probability mass function (PMF) for a degenerate distribution\n with mean `μ`.\n"
base.dists.degenerate.pmf.factory,"\nbase.dists.degenerate.pmf.factory( μ:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n"
base.dists.degenerate.quantile,"\nbase.dists.degenerate.quantile( p:number, μ:number )\n Evaluates the quantile function for a degenerate distribution with mean `μ`.\n"
base.dists.degenerate.quantile.factory,"\nbase.dists.degenerate.quantile.factory( μ:number )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n"
base.dists.degenerate.stdev,"\nbase.dists.degenerate.stdev( μ:number )\n Returns the standard deviation of a degenerate distribution with constant\n value `μ`.\n"
base.dists.degenerate.variance,"\nbase.dists.degenerate.variance( μ:number )\n Returns the variance of a degenerate distribution with constant value `μ`.\n"
base.dists.discreteUniform.cdf,"\nbase.dists.discreteUniform.cdf( x:number, a:integer, b:integer )\n Evaluates the cumulative distribution function (CDF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n"
base.dists.discreteUniform.cdf.factory,"\nbase.dists.discreteUniform.cdf.factory( a:integer, b:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n"
base.dists.discreteUniform.DiscreteUniform,"\nbase.dists.discreteUniform.DiscreteUniform( [a:integer, b:integer] )\n Returns a discrete uniform distribution object.\n"
base.dists.discreteUniform.entropy,"\nbase.dists.discreteUniform.entropy( a:integer, b:integer )\n Returns the entropy of a discrete uniform distribution.\n"
base.dists.discreteUniform.kurtosis,"\nbase.dists.discreteUniform.kurtosis( a:integer, b:integer )\n Returns the excess kurtosis of a discrete uniform distribution.\n"
base.dists.discreteUniform.logcdf,"\nbase.dists.discreteUniform.logcdf( x:number, a:integer, b:integer )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a discrete uniform distribution with minimum support `a` and\n maximum support `b` at a value `x`.\n"
base.dists.discreteUniform.logcdf.factory,"\nbase.dists.discreteUniform.logcdf.factory( a:integer, b:integer )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n"
base.dists.discreteUniform.logpmf,"\nbase.dists.discreteUniform.logpmf( x:number, a:integer, b:integer )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n discrete uniform distribution with minimum support `a` and maximum support\n `b` at a value `x`.\n"
base.dists.discreteUniform.logpmf.factory,"\nbase.dists.discreteUniform.logpmf.factory( a:integer, b:integer )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n"
base.dists.discreteUniform.mean,"\nbase.dists.discreteUniform.mean( a:integer, b:integer )\n Returns the expected value of a discrete uniform distribution.\n"
base.dists.discreteUniform.median,"\nbase.dists.discreteUniform.median( a:integer, b:integer )\n Returns the median of a discrete uniform distribution.\n"
base.dists.discreteUniform.mgf,"\nbase.dists.discreteUniform.mgf( t:number, a:integer, b:integer )\n Evaluates the moment-generating function (MGF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n"
base.dists.discreteUniform.mgf.factory,"\nbase.dists.discreteUniform.mgf.factory( a:integer, b:integer )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n"
base.dists.discreteUniform.pmf,"\nbase.dists.discreteUniform.pmf( x:number, a:integer, b:integer )\n Evaluates the probability mass function (PMF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n"
base.dists.discreteUniform.pmf.factory,"\nbase.dists.discreteUniform.pmf.factory( a:integer, b:integer )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n"
base.dists.discreteUniform.quantile,"\nbase.dists.discreteUniform.quantile( p:number, a:integer, b:integer )\n Evaluates the quantile function for a discrete uniform distribution with\n minimum support `a` and maximum support `b` at a probability `p`.\n"
base.dists.discreteUniform.quantile.factory,"\nbase.dists.discreteUniform.quantile.factory( a:integer, b:integer )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n"
base.dists.discreteUniform.skewness,"\nbase.dists.discreteUniform.skewness( a:integer, b:integer )\n Returns the skewness of a discrete uniform distribution.\n"
base.dists.discreteUniform.stdev,"\nbase.dists.discreteUniform.stdev( a:integer, b:integer )\n Returns the standard deviation of a discrete uniform distribution.\n"
base.dists.discreteUniform.variance,"\nbase.dists.discreteUniform.variance( a:integer, b:integer )\n Returns the variance of a discrete uniform distribution.\n"
base.dists.erlang.cdf,"\nbase.dists.erlang.cdf( x:number, k:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for an Erlang\n distribution with shape parameter `k` and rate parameter `λ` at a value\n `x`.\n"
base.dists.erlang.cdf.factory,"\nbase.dists.erlang.cdf.factory( k:number, λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n"
base.dists.erlang.entropy,"\nbase.dists.erlang.entropy( k:integer, λ:number )\n Returns the differential entropy of an Erlang distribution (in nats).\n"
base.dists.erlang.Erlang,"\nbase.dists.erlang.Erlang( [k:number, λ:number] )\n Returns an Erlang distribution object.\n"
base.dists.erlang.kurtosis,"\nbase.dists.erlang.kurtosis( k:integer, λ:number )\n Returns the excess kurtosis of an Erlang distribution.\n"
base.dists.erlang.logpdf,"\nbase.dists.erlang.logpdf( x:number, k:number, λ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n at a value `x`.\n"
base.dists.erlang.logpdf.factory,"\nbase.dists.erlang.logpdf.factory( k:number, λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n"
base.dists.erlang.mean,"\nbase.dists.erlang.mean( k:integer, λ:number )\n Returns the expected value of an Erlang distribution.\n"
base.dists.erlang.mgf,"\nbase.dists.erlang.mgf( t:number, k:number, λ:number )\n Evaluates the moment-generating function (MGF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `t`.\n"
base.dists.erlang.mgf.factory,"\nbase.dists.erlang.mgf.factory( k:number, λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n"
base.dists.erlang.mode,"\nbase.dists.erlang.mode( k:integer, λ:number )\n Returns the mode of an Erlang distribution.\n"
base.dists.erlang.pdf,"\nbase.dists.erlang.pdf( x:number, k:number, λ:number )\n Evaluates the probability density function (PDF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `x`.\n"
base.dists.erlang.pdf.factory,"\nbase.dists.erlang.pdf.factory( k:number, λ:number )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n"
base.dists.erlang.quantile,"\nbase.dists.erlang.quantile( p:number, k:number, λ:number )\n Evaluates the quantile function for an Erlang distribution with shape\n parameter `k` and rate parameter `λ` at a probability `p`.\n"
base.dists.erlang.quantile.factory,"\nbase.dists.erlang.quantile.factory( k:number, λ:number )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n"
base.dists.erlang.skewness,"\nbase.dists.erlang.skewness( k:integer, λ:number )\n Returns the skewness of an Erlang distribution.\n"
base.dists.erlang.stdev,"\nbase.dists.erlang.stdev( k:integer, λ:number )\n Returns the standard deviation of an Erlang distribution.\n"
base.dists.erlang.variance,"\nbase.dists.erlang.variance( k:integer, λ:number )\n Returns the variance of an Erlang distribution.\n"
base.dists.exponential.cdf,"\nbase.dists.exponential.cdf( x:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n"
base.dists.exponential.cdf.factory,"\nbase.dists.exponential.cdf.factory( λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n"
base.dists.exponential.entropy,"\nbase.dists.exponential.entropy( λ:number )\n Returns the differential entropy of an exponential distribution.\n"
base.dists.exponential.Exponential,"\nbase.dists.exponential.Exponential( [λ:number] )\n Returns an exponential distribution object.\n"
base.dists.exponential.kurtosis,"\nbase.dists.exponential.kurtosis( λ:number )\n Returns the excess kurtosis of an exponential distribution.\n"
base.dists.exponential.logcdf,"\nbase.dists.exponential.logcdf( x:number, λ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an exponential distribution with rate parameter `λ` at a value\n `x`.\n"
base.dists.exponential.logcdf.factory,"\nbase.dists.exponential.logcdf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n"
base.dists.exponential.logpdf,"\nbase.dists.exponential.logpdf( x:number, λ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an exponential distribution with rate parameter `λ` at a value `x`.\n"
base.dists.exponential.logpdf.factory,"\nbase.dists.exponential.logpdf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n"
base.dists.exponential.mean,"\nbase.dists.exponential.mean( λ:number )\n Returns the expected value of an exponential distribution.\n"
base.dists.exponential.median,"\nbase.dists.exponential.median( λ:number )\n Returns the median of an exponential distribution.\n"
base.dists.exponential.mgf,"\nbase.dists.exponential.mgf( t:number, λ:number )\n Evaluates the moment-generating function (MGF) for an exponential\n distribution with rate parameter `λ` at a value `t`.\n"
base.dists.exponential.mgf.factory,"\nbase.dists.exponential.mgf.factory( λ:number )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n"
base.dists.exponential.mode,"\nbase.dists.exponential.mode( λ:number )\n Returns the mode of an exponential distribution.\n"
base.dists.exponential.pdf,"\nbase.dists.exponential.pdf( x:number, λ:number )\n Evaluates the probability density function (PDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n"
base.dists.exponential.pdf.factory,"\nbase.dists.exponential.pdf.factory( λ:number )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n"
base.dists.exponential.quantile,"\nbase.dists.exponential.quantile( p:number, λ:number )\n Evaluates the quantile function for an exponential distribution with rate\n parameter `λ` at a probability `p`.\n"
base.dists.exponential.quantile.factory,"\nbase.dists.exponential.quantile.factory( λ:number )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n"
base.dists.exponential.skewness,"\nbase.dists.exponential.skewness( λ:number )\n Returns the skewness of an exponential distribution.\n"
base.dists.exponential.stdev,"\nbase.dists.exponential.stdev( λ:number )\n Returns the standard deviation of an exponential distribution.\n"
base.dists.exponential.variance,"\nbase.dists.exponential.variance( λ:number )\n Returns the variance of an exponential distribution.\n"
base.dists.f.cdf,"\nbase.dists.f.cdf( x:number, d1:number, d2:number )\n Evaluates the cumulative distribution function (CDF) for an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2` at a value `x`.\n"
base.dists.f.cdf.factory,"\nbase.dists.f.cdf.factory( d1:number, d2:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n"
base.dists.f.entropy,"\nbase.dists.f.entropy( d1:number, d2:number )\n Returns the differential entropy of an F distribution (in nats).\n"
base.dists.f.F,"\nbase.dists.f.F( [d1:number, d2:number] )\n Returns an F distribution object.\n"
base.dists.f.kurtosis,"\nbase.dists.f.kurtosis( d1:number, d2:number )\n Returns the excess kurtosis of an F distribution.\n"
base.dists.f.mean,"\nbase.dists.f.mean( d1:number, d2:number )\n Returns the expected value of an F distribution.\n"
base.dists.f.mode,"\nbase.dists.f.mode( d1:number, d2:number )\n Returns the mode of an F distribution.\n"
base.dists.f.pdf,"\nbase.dists.f.pdf( x:number, d1:number, d2:number )\n Evaluates the probability density function (PDF) for an F distribution with\n numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n a value `x`.\n"
base.dists.f.pdf.factory,"\nbase.dists.f.pdf.factory( d1:number, d2:number )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n"
base.dists.f.quantile,"\nbase.dists.f.quantile( p:number, d1:number, d2:number )\n Evaluates the quantile function for an F distribution with numerator degrees\n of freedom `d1` and denominator degrees of freedom `d2` at a probability\n `p`.\n"
base.dists.f.quantile.factory,"\nbase.dists.f.quantile.factory( d1:number, d2:number )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n"
base.dists.f.skewness,"\nbase.dists.f.skewness( d1:number, d2:number )\n Returns the skewness of an F distribution.\n"
base.dists.f.stdev,"\nbase.dists.f.stdev( d1:number, d2:number )\n Returns the standard deviation of an F distribution.\n"
base.dists.f.variance,"\nbase.dists.f.variance( d1:number, d2:number )\n Returns the variance of an F distribution.\n"
base.dists.frechet.cdf,"\nbase.dists.frechet.cdf( x:number, α:number, s:number, m:number )\n Evaluates the cumulative distribution function (CDF) for a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n"
base.dists.frechet.cdf.factory,"\nbase.dists.frechet.cdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n"
base.dists.frechet.entropy,"\nbase.dists.frechet.entropy( α:number, s:number, m:number )\n Returns the differential entropy of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m` (in nats).\n"
base.dists.frechet.Frechet,"\nbase.dists.frechet.Frechet( [α:number, s:number, m:number] )\n Returns a Fréchet distribution object.\n"
base.dists.frechet.kurtosis,"\nbase.dists.frechet.kurtosis( α:number, s:number, m:number )\n Returns the excess kurtosis of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n"
base.dists.frechet.logcdf,"\nbase.dists.frechet.logcdf( x:number, α:number, s:number, m:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n `s`, and location `m`.\n"
base.dists.frechet.logcdf.factory,"\nbase.dists.frechet.logcdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n"
base.dists.frechet.logpdf,"\nbase.dists.frechet.logpdf( x:number, α:number, s:number, m:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n"
base.dists.frechet.logpdf.factory,"\nbase.dists.frechet.logpdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n"
base.dists.frechet.mean,"\nbase.dists.frechet.mean( α:number, s:number, m:number )\n Returns the expected value of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n"
base.dists.frechet.median,"\nbase.dists.frechet.median( α:number, s:number, m:number )\n Returns the median of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n"
base.dists.frechet.mode,"\nbase.dists.frechet.mode( α:number, s:number, m:number )\n Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n"
base.dists.frechet.pdf,"\nbase.dists.frechet.pdf( x:number, α:number, s:number, m:number )\n Evaluates the probability density function (PDF) for a Fréchet distribution\n with shape parameter `α`, scale parameter `s`, and location `m`.\n"
base.dists.frechet.pdf.factory,"\nbase.dists.frechet.pdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n"
base.dists.frechet.quantile,"\nbase.dists.frechet.quantile( p:number, α:number, s:number, m:number )\n Evaluates the quantile function for a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n"
base.dists.frechet.quantile.factory,"\nbase.dists.frechet.quantile.factory( α:number, s:number, m:number )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n"
base.dists.frechet.skewness,"\nbase.dists.frechet.skewness( α:number, s:number, m:number )\n Returns the skewness of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n"
base.dists.frechet.stdev,"\nbase.dists.frechet.stdev( α:number, s:number, m:number )\n Returns the standard deviation of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n"
base.dists.frechet.variance,"\nbase.dists.frechet.variance( α:number, s:number, m:number )\n Returns the variance of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n"
base.dists.gamma.cdf,"\nbase.dists.gamma.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a gamma\n distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n"
base.dists.gamma.cdf.factory,"\nbase.dists.gamma.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n"
base.dists.gamma.entropy,"\nbase.dists.gamma.entropy( α:number, β:number )\n Returns the differential entropy of a gamma distribution.\n"
base.dists.gamma.Gamma,"\nbase.dists.gamma.Gamma( [α:number, β:number] )\n Returns a gamma distribution object.\n"
base.dists.gamma.kurtosis,"\nbase.dists.gamma.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a gamma distribution.\n"
base.dists.gamma.logcdf,"\nbase.dists.gamma.logcdf( x:number, α:number, β:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n"
base.dists.gamma.logcdf.factory,"\nbase.dists.gamma.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n"
base.dists.gamma.logpdf,"\nbase.dists.gamma.logpdf( x:number, α:number, β:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n"
base.dists.gamma.logpdf.factory,"\nbase.dists.gamma.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n"
base.dists.gamma.mean,"\nbase.dists.gamma.mean( α:number, β:number )\n Returns the expected value of a gamma distribution.\n"
base.dists.gamma.mgf,"\nbase.dists.gamma.mgf( t:number, α:number, β:number )\n Evaluates the moment-generating function (MGF) for a gamma distribution with\n shape parameter `α` and rate parameter `β` at a value `t`.\n"
base.dists.gamma.mgf.factory,"\nbase.dists.gamma.mgf.factory( α:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n"
base.dists.gamma.mode,"\nbase.dists.gamma.mode( α:number, β:number )\n Returns the mode of a gamma distribution.\n"
base.dists.gamma.pdf,"\nbase.dists.gamma.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a gamma distribution\n with shape parameter `α` and rate parameter `β` at a value `x`.\n"
base.dists.gamma.pdf.factory,"\nbase.dists.gamma.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n"
base.dists.gamma.quantile,"\nbase.dists.gamma.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a gamma distribution with shape\n parameter `α` and rate parameter `β` at a probability `p`.\n"
base.dists.gamma.quantile.factory,"\nbase.dists.gamma.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n"
base.dists.gamma.skewness,"\nbase.dists.gamma.skewness( α:number, β:number )\n Returns the skewness of a gamma distribution.\n"
base.dists.gamma.stdev,"\nbase.dists.gamma.stdev( α:number, β:number )\n Returns the standard deviation of a gamma distribution.\n"
base.dists.gamma.variance,"\nbase.dists.gamma.variance( α:number, β:number )\n Returns the variance of a gamma distribution.\n"
base.dists.geometric.cdf,"\nbase.dists.geometric.cdf( x:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a geometric\n distribution with success probability `p` at a value `x`.\n"
base.dists.geometric.cdf.factory,"\nbase.dists.geometric.cdf.factory( p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n"
base.dists.geometric.entropy,"\nbase.dists.geometric.entropy( p:number )\n Returns the entropy of a geometric distribution with success probability\n `p` (in nats).\n"
base.dists.geometric.Geometric,"\nbase.dists.geometric.Geometric( [p:number] )\n Returns a geometric distribution object.\n"
base.dists.geometric.kurtosis,"\nbase.dists.geometric.kurtosis( p:number )\n Returns the excess kurtosis of a geometric distribution with success\n probability `p`.\n"
base.dists.geometric.logcdf,"\nbase.dists.geometric.logcdf( x:number, p:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n geometric distribution with success probability `p` at a value `x`.\n"
base.dists.geometric.logcdf.factory,"\nbase.dists.geometric.logcdf.factory( p:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n"
base.dists.geometric.logpmf,"\nbase.dists.geometric.logpmf( x:number, p:number )\n Evaluates the logarithm of the probability mass function (PMF) for a\n geometric distribution with success probability `p` at a value `x`.\n"
base.dists.geometric.logpmf.factory,"\nbase.dists.geometric.logpmf.factory( p:number )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n"
base.dists.geometric.mean,"\nbase.dists.geometric.mean( p:number )\n Returns the expected value of a geometric distribution with success\n probability `p`.\n"
base.dists.geometric.median,"\nbase.dists.geometric.median( p:number )\n Returns the median of a geometric distribution with success probability `p`.\n"
base.dists.geometric.mgf,"\nbase.dists.geometric.mgf( t:number, p:number )\n Evaluates the moment-generating function (MGF) for a geometric\n distribution with success probability `p` at a value `t`.\n"
base.dists.geometric.mgf.factory,"\nbase.dists.geometric.mgf.factory( p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n"
base.dists.geometric.mode,"\nbase.dists.geometric.mode( p:number )\n Returns the mode of a geometric distribution with success probability `p`.\n"
base.dists.geometric.pmf,"\nbase.dists.geometric.pmf( x:number, p:number )\n Evaluates the probability mass function (PMF) for a geometric distribution\n with success probability `p` at a value `x`.\n"
base.dists.geometric.pmf.factory,"\nbase.dists.geometric.pmf.factory( p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n"
base.dists.geometric.quantile,"\nbase.dists.geometric.quantile( r:number, p:number )\n Evaluates the quantile function for a geometric distribution with success\n probability `p` at a probability `r`.\n"
base.dists.geometric.quantile.factory,"\nbase.dists.geometric.quantile.factory( p:number )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n"
base.dists.geometric.skewness,"\nbase.dists.geometric.skewness( p:number )\n Returns the skewness of a geometric distribution with success probability\n `p`.\n"
base.dists.geometric.stdev,"\nbase.dists.geometric.stdev( p:number )\n Returns the standard deviation of a geometric distribution with success\n probability `p`.\n"
base.dists.geometric.variance,"\nbase.dists.geometric.variance( p:number )\n Returns the variance of a geometric distribution with success probability\n `p`.\n"
base.dists.gumbel.cdf,"\nbase.dists.gumbel.cdf( x:number, μ:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a Gumbel\n distribution with location parameter `μ` and scale parameter `β` at a value\n `x`.\n"
base.dists.gumbel.cdf.factory,"\nbase.dists.gumbel.cdf.factory( μ:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n"
base.dists.gumbel.entropy,"\nbase.dists.gumbel.entropy( μ:number, β:number )\n Returns the differential entropy of a Gumbel distribution with location\n parameter `μ` and scale parameter `β` (in nats).\n"
base.dists.gumbel.Gumbel,"\nbase.dists.gumbel.Gumbel( [μ:number, β:number] )\n Returns a Gumbel distribution object.\n"
base.dists.gumbel.kurtosis,"\nbase.dists.gumbel.kurtosis( μ:number, β:number )\n Returns the excess kurtosis of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n"
base.dists.gumbel.logcdf,"\nbase.dists.gumbel.logcdf( x:number, μ:number, β:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n"
base.dists.gumbel.logcdf.factory,"\nbase.dists.gumbel.logcdf.factory( μ:number, β:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n"
base.dists.gumbel.logpdf,"\nbase.dists.gumbel.logpdf( x:number, μ:number, β:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n"
base.dists.gumbel.logpdf.factory,"\nbase.dists.gumbel.logpdf.factory( μ:number, β:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n"
base.dists.gumbel.mean,"\nbase.dists.gumbel.mean( μ:number, β:number )\n Returns the expected value of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n"
base.dists.gumbel.median,"\nbase.dists.gumbel.median( μ:number, β:number )\n Returns the median of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n"
base.dists.gumbel.mgf,"\nbase.dists.gumbel.mgf( t:number, μ:number, β:number )\n Evaluates the moment-generating function (MGF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `t`.\n"
base.dists.gumbel.mgf.factory,"\nbase.dists.gumbel.mgf.factory( μ:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n"
base.dists.gumbel.mode,"\nbase.dists.gumbel.mode( μ:number, β:number )\n Returns the mode of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n"
base.dists.gumbel.pdf,"\nbase.dists.gumbel.pdf( x:number, μ:number, β:number )\n Evaluates the probability density function (PDF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `x`.\n"
base.dists.gumbel.pdf.factory,"\nbase.dists.gumbel.pdf.factory( μ:number, β:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n"
base.dists.gumbel.quantile,"\nbase.dists.gumbel.quantile( p:number, μ:number, β:number )\n Evaluates the quantile function for a Gumbel distribution with location\n parameter `μ` and scale parameter `β` at a probability `p`.\n"
base.dists.gumbel.quantile.factory,"\nbase.dists.gumbel.quantile.factory( μ:number, β:number )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n"
base.dists.gumbel.skewness,"\nbase.dists.gumbel.skewness( μ:number, β:number )\n Returns the skewness of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n"
base.dists.gumbel.stdev,"\nbase.dists.gumbel.stdev( μ:number, β:number )\n Returns the standard deviation of a Gumbel distribution with location\n parameter `μ` and scale parameter `β`.\n"
base.dists.gumbel.variance,"\nbase.dists.gumbel.variance( μ:number, β:number )\n Returns the variance of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n"
base.dists.hypergeometric.cdf,"\nbase.dists.hypergeometric.cdf( x:number, N:integer, K:integer, n:integer )\n Evaluates the cumulative distribution function (CDF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n"
base.dists.hypergeometric.cdf.factory,"\nbase.dists.hypergeometric.cdf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n"
base.dists.hypergeometric.Hypergeometric,"\nbase.dists.hypergeometric.Hypergeometric( [N:integer, K:integer, n:integer] )\n Returns a hypergeometric distribution object.\n"
base.dists.hypergeometric.kurtosis,"\nbase.dists.hypergeometric.kurtosis( N:integer, K:integer, n:integer )\n Returns the excess kurtosis of a hypergeometric distribution.\n"
base.dists.hypergeometric.logpmf,"\nbase.dists.hypergeometric.logpmf( x:number, N:integer, K:integer, n:integer )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n` at a value `x`.\n"
base.dists.hypergeometric.logpmf.factory,"\nbase.dists.hypergeometric.logpmf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n"
base.dists.hypergeometric.mean,"\nbase.dists.hypergeometric.mean( N:integer, K:integer, n:integer )\n Returns the expected value of a hypergeometric distribution.\n"
base.dists.hypergeometric.mode,"\nbase.dists.hypergeometric.mode( N:integer, K:integer, n:integer )\n Returns the mode of a hypergeometric distribution.\n"
base.dists.hypergeometric.pmf,"\nbase.dists.hypergeometric.pmf( x:number, N:integer, K:integer, n:integer )\n Evaluates the probability mass function (PMF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n"
base.dists.hypergeometric.pmf.factory,"\nbase.dists.hypergeometric.pmf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n"
base.dists.hypergeometric.quantile,"\nbase.dists.hypergeometric.quantile( p:number, N:integer, K:integer, n:integer )\n Evaluates the quantile function for a hypergeometric distribution with\n population size `N`, subpopulation size `K`, and number of draws `n` at a\n probability `p`.\n"
base.dists.hypergeometric.quantile.factory,"\nbase.dists.hypergeometric.quantile.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n"
base.dists.hypergeometric.skewness,"\nbase.dists.hypergeometric.skewness( N:integer, K:integer, n:integer )\n Returns the skewness of a hypergeometric distribution.\n"
base.dists.hypergeometric.stdev,"\nbase.dists.hypergeometric.stdev( N:integer, K:integer, n:integer )\n Returns the standard deviation of a hypergeometric distribution.\n"
base.dists.hypergeometric.variance,"\nbase.dists.hypergeometric.variance( N:integer, K:integer, n:integer )\n Returns the variance of a hypergeometric distribution.\n"
base.dists.invgamma.cdf,"\nbase.dists.invgamma.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n"
base.dists.invgamma.cdf.factory,"\nbase.dists.invgamma.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n"
base.dists.invgamma.entropy,"\nbase.dists.invgamma.entropy( α:number, β:number )\n Returns the differential entropy of an inverse gamma distribution.\n"
base.dists.invgamma.InvGamma,"\nbase.dists.invgamma.InvGamma( [α:number, β:number] )\n Returns an inverse gamma distribution object.\n"
base.dists.invgamma.kurtosis,"\nbase.dists.invgamma.kurtosis( α:number, β:number )\n Returns the excess kurtosis of an inverse gamma distribution.\n"
base.dists.invgamma.logpdf,"\nbase.dists.invgamma.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an inverse gamma distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n"
base.dists.invgamma.logpdf.factory,"\nbase.dists.invgamma.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n"
base.dists.invgamma.mean,"\nbase.dists.invgamma.mean( α:number, β:number )\n Returns the expected value of an inverse gamma distribution.\n"
base.dists.invgamma.mode,"\nbase.dists.invgamma.mode( α:number, β:number )\n Returns the mode of an inverse gamma distribution.\n"
base.dists.invgamma.pdf,"\nbase.dists.invgamma.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n"
base.dists.invgamma.pdf.factory,"\nbase.dists.invgamma.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n"
base.dists.invgamma.quantile,"\nbase.dists.invgamma.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β` at a probability `p`.\n"
base.dists.invgamma.quantile.factory,"\nbase.dists.invgamma.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n"
base.dists.invgamma.skewness,"\nbase.dists.invgamma.skewness( α:number, β:number )\n Returns the skewness of an inverse gamma distribution.\n"
base.dists.invgamma.stdev,"\nbase.dists.invgamma.stdev( α:number, β:number )\n Returns the standard deviation of an inverse gamma distribution.\n"
base.dists.invgamma.variance,"\nbase.dists.invgamma.variance( α:number, β:number )\n Returns the variance of an inverse gamma distribution.\n"
base.dists.kumaraswamy.cdf,"\nbase.dists.kumaraswamy.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n"
base.dists.kumaraswamy.cdf.factory,"\nbase.dists.kumaraswamy.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n"
base.dists.kumaraswamy.Kumaraswamy,"\nbase.dists.kumaraswamy.Kumaraswamy( [a:number, b:number] )\n Returns a Kumaraswamy's double bounded distribution object.\n"
base.dists.kumaraswamy.kurtosis,"\nbase.dists.kumaraswamy.kurtosis( a:number, b:number )\n Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n"
base.dists.kumaraswamy.logcdf,"\nbase.dists.kumaraswamy.logcdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for Kumaraswamy's double bounded distribution with first shape\n parameter `a` and second shape parameter `b` at a value `x`.\n"
base.dists.kumaraswamy.logcdf.factory,"\nbase.dists.kumaraswamy.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n"
base.dists.kumaraswamy.logpdf,"\nbase.dists.kumaraswamy.logpdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for Kumaraswamy's double bounded distribution with first shape parameter `a`\n and second shape parameter `b` at a value `x`.\n"
base.dists.kumaraswamy.logpdf.factory,"\nbase.dists.kumaraswamy.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n"
base.dists.kumaraswamy.mean,"\nbase.dists.kumaraswamy.mean( a:number, b:number )\n Returns the mean of a Kumaraswamy's double bounded distribution.\n"
base.dists.kumaraswamy.median,"\nbase.dists.kumaraswamy.median( a:number, b:number )\n Returns the median of a Kumaraswamy's double bounded distribution.\n"
base.dists.kumaraswamy.mode,"\nbase.dists.kumaraswamy.mode( a:number, b:number )\n Returns the mode of a Kumaraswamy's double bounded distribution.\n"
base.dists.kumaraswamy.pdf,"\nbase.dists.kumaraswamy.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for Kumaraswamy's double\n bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n"
base.dists.kumaraswamy.pdf.factory,"\nbase.dists.kumaraswamy.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n"
base.dists.kumaraswamy.quantile,"\nbase.dists.kumaraswamy.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for a Kumaraswamy's double bounded\n distribution with first shape parameter `a` and second shape parameter `b`\n at a probability `p`.\n"
base.dists.kumaraswamy.quantile.factory,"\nbase.dists.kumaraswamy.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n"
base.dists.kumaraswamy.skewness,"\nbase.dists.kumaraswamy.skewness( a:number, b:number )\n Returns the skewness of a Kumaraswamy's double bounded distribution.\n"
base.dists.kumaraswamy.stdev,"\nbase.dists.kumaraswamy.stdev( a:number, b:number )\n Returns the standard deviation of a Kumaraswamy's double bounded\n distribution.\n"
base.dists.kumaraswamy.variance,"\nbase.dists.kumaraswamy.variance( a:number, b:number )\n Returns the variance of a Kumaraswamy's double bounded distribution.\n"
base.dists.laplace.cdf,"\nbase.dists.laplace.cdf( x:number, μ:number, b:number )\n Evaluates the cumulative distribution function (CDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n"
base.dists.laplace.cdf.factory,"\nbase.dists.laplace.cdf.factory( μ:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n"
base.dists.laplace.entropy,"\nbase.dists.laplace.entropy( μ:number, b:number )\n Returns the differential entropy of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n"
base.dists.laplace.kurtosis,"\nbase.dists.laplace.kurtosis( μ:number, b:number )\n Returns the excess kurtosis of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n"
base.dists.laplace.Laplace,"\nbase.dists.laplace.Laplace( [μ:number, b:number] )\n Returns a Laplace distribution object.\n"
base.dists.laplace.logcdf,"\nbase.dists.laplace.logcdf( x:number, μ:number, b:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n"
base.dists.laplace.logcdf.factory,"\nbase.dists.laplace.logcdf.factory( μ:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n"
base.dists.laplace.logpdf,"\nbase.dists.laplace.logpdf( x:number, μ:number, b:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n"
base.dists.laplace.logpdf.factory,"\nbase.dists.laplace.logpdf.factory( μ:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n"
base.dists.laplace.mean,"\nbase.dists.laplace.mean( μ:number, b:number )\n Returns the expected value of a Laplace distribution with location parameter\n `μ` and scale parameter `b`.\n"
base.dists.laplace.median,"\nbase.dists.laplace.median( μ:number, b:number )\n Returns the median of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n"
base.dists.laplace.mgf,"\nbase.dists.laplace.mgf( t:number, μ:number, b:number )\n Evaluates the moment-generating function (MGF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `t`.\n"
base.dists.laplace.mgf.factory,"\nbase.dists.laplace.mgf.factory( μ:number, b:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n"
base.dists.laplace.mode,"\nbase.dists.laplace.mode( μ:number, b:number )\n Returns the mode of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n"
base.dists.laplace.pdf,"\nbase.dists.laplace.pdf( x:number, μ:number, b:number )\n Evaluates the probability density function (PDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n"
base.dists.laplace.pdf.factory,"\nbase.dists.laplace.pdf.factory( μ:number, b:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n"
base.dists.laplace.quantile,"\nbase.dists.laplace.quantile( p:number, μ:number, b:number )\n Evaluates the quantile function for a Laplace distribution with scale\n parameter `b` and location parameter `μ` at a probability `p`.\n"
base.dists.laplace.quantile.factory,"\nbase.dists.laplace.quantile.factory( μ:number, b:number )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n"
base.dists.laplace.skewness,"\nbase.dists.laplace.skewness( μ:number, b:number )\n Returns the skewness of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n"
base.dists.laplace.stdev,"\nbase.dists.laplace.stdev( μ:number, b:number )\n Returns the standard deviation of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n"
base.dists.laplace.variance,"\nbase.dists.laplace.variance( μ:number, b:number )\n Returns the variance of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n"
base.dists.levy.cdf,"\nbase.dists.levy.cdf( x:number, μ:number, c:number )\n Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n"
base.dists.levy.cdf.factory,"\nbase.dists.levy.cdf.factory( μ:number, c:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n"
base.dists.levy.entropy,"\nbase.dists.levy.entropy( μ:number, c:number )\n Returns the differential entropy of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n"
base.dists.levy.Levy,"\nbase.dists.levy.Levy( [μ:number, c:number] )\n Returns a Lévy distribution object.\n"
base.dists.levy.logcdf,"\nbase.dists.levy.logcdf( x:number, μ:number, c:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Lévy distribution with location parameter `μ` and scale parameter `c` at a\n value `x`.\n"
base.dists.levy.logcdf.factory,"\nbase.dists.levy.logcdf.factory( μ:number, c:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n"
base.dists.levy.logpdf,"\nbase.dists.levy.logpdf( x:number, μ:number, c:number )\n Evaluates the logarithm of the probability density function (PDF) for a Lévy\n distribution with location parameter `μ` and scale parameter `c` at a value\n `x`.\n"
base.dists.levy.logpdf.factory,"\nbase.dists.levy.logpdf.factory( μ:number, c:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n"
base.dists.levy.mean,"\nbase.dists.levy.mean( μ:number, c:number )\n Returns the expected value of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n"
base.dists.levy.median,"\nbase.dists.levy.median( μ:number, c:number )\n Returns the median of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n"
base.dists.levy.mode,"\nbase.dists.levy.mode( μ:number, c:number )\n Returns the mode of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n"
base.dists.levy.pdf,"\nbase.dists.levy.pdf( x:number, μ:number, c:number )\n Evaluates the probability density function (PDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n"
base.dists.levy.pdf.factory,"\nbase.dists.levy.pdf.factory( μ:number, c:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n"
base.dists.levy.quantile,"\nbase.dists.levy.quantile( p:number, μ:number, c:number )\n Evaluates the quantile function for a Lévy distribution with location\n parameter `μ` and scale parameter `c` at a probability `p`.\n"
base.dists.levy.quantile.factory,"\nbase.dists.levy.quantile.factory( μ:number, c:number )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n"
base.dists.levy.stdev,"\nbase.dists.levy.stdev( μ:number, c:number )\n Returns the standard deviation of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n"
base.dists.levy.variance,"\nbase.dists.levy.variance( μ:number, c:number )\n Returns the variance of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n"
base.dists.logistic.cdf,"\nbase.dists.logistic.cdf( x:number, μ:number, s:number )\n Evaluates the cumulative distribution function (CDF) for a logistic\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n"
base.dists.logistic.cdf.factory,"\nbase.dists.logistic.cdf.factory( μ:number, s:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n"
base.dists.logistic.entropy,"\nbase.dists.logistic.entropy( μ:number, s:number )\n Returns the differential entropy of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n"
base.dists.logistic.kurtosis,"\nbase.dists.logistic.kurtosis( μ:number, s:number )\n Returns the excess kurtosis of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n"
base.dists.logistic.logcdf,"\nbase.dists.logistic.logcdf( x:number, μ:number, s:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n"
base.dists.logistic.logcdf.factory,"\nbase.dists.logistic.logcdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n"
base.dists.logistic.Logistic,"\nbase.dists.logistic.Logistic( [μ:number, s:number] )\n Returns a logistic distribution object.\n"
base.dists.logistic.logpdf,"\nbase.dists.logistic.logpdf( x:number, μ:number, s:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n"
base.dists.logistic.logpdf.factory,"\nbase.dists.logistic.logpdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n"
base.dists.logistic.mean,"\nbase.dists.logistic.mean( μ:number, s:number )\n Returns the expected value of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n"
base.dists.logistic.median,"\nbase.dists.logistic.median( μ:number, s:number )\n Returns the median of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n"
base.dists.logistic.mgf,"\nbase.dists.logistic.mgf( t:number, μ:number, s:number )\n Evaluates the moment-generating function (MGF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `t`.\n"
base.dists.logistic.mgf.factory,"\nbase.dists.logistic.mgf.factory( μ:number, s:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n"
base.dists.logistic.mode,"\nbase.dists.logistic.mode( μ:number, s:number )\n Returns the mode of a logistic distribution with location parameter `μ` and\n scale parameter `s`.\n"
base.dists.logistic.pdf,"\nbase.dists.logistic.pdf( x:number, μ:number, s:number )\n Evaluates the probability density function (PDF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `x`.\n"
base.dists.logistic.pdf.factory,"\nbase.dists.logistic.pdf.factory( μ:number, s:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n"
base.dists.logistic.quantile,"\nbase.dists.logistic.quantile( p:number, μ:number, s:number )\n Evaluates the quantile function for a logistic distribution with location\n parameter `μ` and scale parameter `s` at a probability `p`.\n"
base.dists.logistic.quantile.factory,"\nbase.dists.logistic.quantile.factory( μ:number, s:number )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n"
base.dists.logistic.skewness,"\nbase.dists.logistic.skewness( μ:number, s:number )\n Returns the skewness of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n"
base.dists.logistic.stdev,"\nbase.dists.logistic.stdev( μ:number, s:number )\n Returns the standard deviation of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n"
base.dists.logistic.variance,"\nbase.dists.logistic.variance( μ:number, s:number )\n Returns the variance of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n"
base.dists.lognormal.cdf,"\nbase.dists.lognormal.cdf( x:number, μ:number, σ:number )\n Evaluates the cumulative distribution function (CDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n"
base.dists.lognormal.cdf.factory,"\nbase.dists.lognormal.cdf.factory( μ:number, σ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n"
base.dists.lognormal.entropy,"\nbase.dists.lognormal.entropy( μ:number, σ:number )\n Returns the differential entropy of a lognormal distribution with location\n `μ` and scale `σ` (in nats).\n"
base.dists.lognormal.kurtosis,"\nbase.dists.lognormal.kurtosis( μ:number, σ:number )\n Returns the excess kurtosis of a lognormal distribution with location `μ`\n and scale `σ`.\n"
base.dists.lognormal.LogNormal,"\nbase.dists.lognormal.LogNormal( [μ:number, σ:number] )\n Returns a lognormal distribution object.\n"
base.dists.lognormal.logcdf,"\nbase.dists.lognormal.logcdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a lognormal distribution with mean `μ` and standard deviation `σ`\n at a value `x`.\n"
base.dists.lognormal.logcdf.factory,"\nbase.dists.lognormal.logcdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with mean `μ` and\n standard deviation `σ`.\n"
base.dists.lognormal.logpdf,"\nbase.dists.lognormal.logpdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a lognormal distribution with location parameter `μ` and scale parameter\n `σ` at a value `x`.\n"
base.dists.lognormal.logpdf.factory,"\nbase.dists.lognormal.logpdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n"
base.dists.lognormal.mean,"\nbase.dists.lognormal.mean( μ:number, σ:number )\n Returns the expected value of a lognormal distribution with location `μ` and\n scale `σ`.\n"
base.dists.lognormal.median,"\nbase.dists.lognormal.median( μ:number, σ:number )\n Returns the median of a lognormal distribution with location `μ` and scale\n `σ`.\n"
base.dists.lognormal.mode,"\nbase.dists.lognormal.mode( μ:number, σ:number )\n Returns the mode of a lognormal distribution with location `μ` and scale\n `σ`.\n"
base.dists.lognormal.pdf,"\nbase.dists.lognormal.pdf( x:number, μ:number, σ:number )\n Evaluates the probability density function (PDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n"
base.dists.lognormal.pdf.factory,"\nbase.dists.lognormal.pdf.factory( μ:number, σ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n"
base.dists.lognormal.quantile,"\nbase.dists.lognormal.quantile( p:number, μ:number, σ:number )\n Evaluates the quantile function for a lognormal distribution with location\n parameter `μ` and scale parameter `σ` at a probability `p`.\n"
base.dists.lognormal.quantile.factory,"\nbase.dists.lognormal.quantile.factory( μ:number, σ:number )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n"
base.dists.lognormal.skewness,"\nbase.dists.lognormal.skewness( μ:number, σ:number )\n Returns the skewness of a lognormal distribution with location `μ` and scale\n `σ`.\n"
base.dists.lognormal.stdev,"\nbase.dists.lognormal.stdev( μ:number, σ:number )\n Returns the standard deviation of a lognormal distribution with location `μ`\n and scale `σ`.\n"
base.dists.lognormal.variance,"\nbase.dists.lognormal.variance( μ:number, σ:number )\n Returns the variance of a lognormal distribution with location `μ` and scale\n `σ`.\n"
base.dists.negativeBinomial.cdf,"\nbase.dists.negativeBinomial.cdf( x:number, r:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n"
base.dists.negativeBinomial.cdf.factory,"\nbase.dists.negativeBinomial.cdf.factory( r:number, p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n"
base.dists.negativeBinomial.kurtosis,"\nbase.dists.negativeBinomial.kurtosis( r:integer, p:number )\n Returns the excess kurtosis of a negative binomial distribution.\n"
base.dists.negativeBinomial.logpmf,"\nbase.dists.negativeBinomial.logpmf( x:number, r:number, p:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p` at a value `x`.\n"
base.dists.negativeBinomial.logpmf.factory,"\nbase.dists.negativeBinomial.logpmf.factory( r:number, p:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n"
base.dists.negativeBinomial.mean,"\nbase.dists.negativeBinomial.mean( r:integer, p:number )\n Returns the expected value of a negative binomial distribution.\n"
base.dists.negativeBinomial.mgf,"\nbase.dists.negativeBinomial.mgf( x:number, r:number, p:number )\n Evaluates the moment-generating function (MGF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `t`.\n"
base.dists.negativeBinomial.mgf.factory,"\nbase.dists.negativeBinomial.mgf.factory( r:number, p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n"
base.dists.negativeBinomial.mode,"\nbase.dists.negativeBinomial.mode( r:integer, p:number )\n Returns the mode of a negative binomial distribution.\n"
base.dists.negativeBinomial.NegativeBinomial,"\nbase.dists.negativeBinomial.NegativeBinomial( [r:number, p:number] )\n Returns a negative binomial distribution object.\n"
base.dists.negativeBinomial.pmf,"\nbase.dists.negativeBinomial.pmf( x:number, r:number, p:number )\n Evaluates the probability mass function (PMF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n"
base.dists.negativeBinomial.pmf.factory,"\nbase.dists.negativeBinomial.pmf.factory( r:number, p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n"
base.dists.negativeBinomial.quantile,"\nbase.dists.negativeBinomial.quantile( k:number, r:number, p:number )\n Evaluates the quantile function for a negative binomial distribution with\n number of successes until experiment is stopped `r` and success probability\n `p` at a probability `k`.\n"
base.dists.negativeBinomial.quantile.factory,"\nbase.dists.negativeBinomial.quantile.factory( r:number, p:number )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n"
base.dists.negativeBinomial.skewness,"\nbase.dists.negativeBinomial.skewness( r:integer, p:number )\n Returns the skewness of a negative binomial distribution.\n"
base.dists.negativeBinomial.stdev,"\nbase.dists.negativeBinomial.stdev( r:integer, p:number )\n Returns the standard deviation of a negative binomial distribution.\n"
base.dists.negativeBinomial.variance,"\nbase.dists.negativeBinomial.variance( r:integer, p:number )\n Returns the variance of a negative binomial distribution.\n"
base.dists.normal.cdf,"\nbase.dists.normal.cdf( x:number, μ:number, σ:number )\n Evaluates the cumulative distribution function (CDF) for a normal\n distribution with mean `μ` and standard deviation `σ` at a value `x`.\n"
base.dists.normal.cdf.factory,"\nbase.dists.normal.cdf.factory( μ:number, σ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n"
base.dists.normal.entropy,"\nbase.dists.normal.entropy( μ:number, σ:number )\n Returns the differential entropy of a normal distribution with mean `μ` and\n standard deviation `σ`.\n"
base.dists.normal.kurtosis,"\nbase.dists.normal.kurtosis( μ:number, σ:number )\n Returns the excess kurtosis of a normal distribution with mean `μ` and\n standard deviation `σ`.\n"
base.dists.normal.logcdf,"\nbase.dists.normal.logcdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n a value `x`.\n"
base.dists.normal.logcdf.factory,"\nbase.dists.normal.logcdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n"
base.dists.normal.logpdf,"\nbase.dists.normal.logpdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a normal distribution with mean `μ` and standard deviation `σ` at a\n value `x`.\n"
base.dists.normal.logpdf.factory,"\nbase.dists.normal.logpdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n"
base.dists.normal.mean,"\nbase.dists.normal.mean( μ:number, σ:number )\n Returns the expected value of a normal distribution with mean `μ` and\n standard deviation `σ`.\n"
base.dists.normal.median,"\nbase.dists.normal.median( μ:number, σ:number )\n Returns the median of a normal distribution with mean `μ` and standard\n deviation `σ`.\n"
base.dists.normal.mgf,"\nbase.dists.normal.mgf( x:number, μ:number, σ:number )\n Evaluates the moment-generating function (MGF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `t`.\n"
base.dists.normal.mgf.factory,"\nbase.dists.normal.mgf.factory( μ:number, σ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n"
base.dists.normal.mode,"\nbase.dists.normal.mode( μ:number, σ:number )\n Returns the mode of a normal distribution with mean `μ` and standard\n deviation `σ`.\n"
base.dists.normal.Normal,"\nbase.dists.normal.Normal( [μ:number, σ:number] )\n Returns a normal distribution object.\n"
base.dists.normal.pdf,"\nbase.dists.normal.pdf( x:number, μ:number, σ:number )\n Evaluates the probability density function (PDF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `x`.\n"
base.dists.normal.pdf.factory,"\nbase.dists.normal.pdf.factory( μ:number, σ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n"
base.dists.normal.quantile,"\nbase.dists.normal.quantile( p:number, μ:number, σ:number )\n Evaluates the quantile function for a normal distribution with mean `μ` and\n standard deviation `σ` at a probability `p`.\n"
base.dists.normal.quantile.factory,"\nbase.dists.normal.quantile.factory( μ:number, σ:number )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n"
base.dists.normal.skewness,"\nbase.dists.normal.skewness( μ:number, σ:number )\n Returns the skewness of a normal distribution with mean `μ` and standard\n deviation `σ`.\n"
base.dists.normal.stdev,"\nbase.dists.normal.stdev( μ:number, σ:number )\n Returns the standard deviation of a normal distribution with mean `μ` and\n standard deviation `σ`.\n"
base.dists.normal.variance,"\nbase.dists.normal.variance( μ:number, σ:number )\n Returns the variance of a normal distribution with mean `μ` and standard\n deviation `σ`.\n"
base.dists.pareto1.cdf,"\nbase.dists.pareto1.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n"
base.dists.pareto1.cdf.factory,"\nbase.dists.pareto1.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n"
base.dists.pareto1.entropy,"\nbase.dists.pareto1.entropy( α:number, β:number )\n Returns the differential entropy of a Pareto (Type I) distribution\n (in nats).\n"
base.dists.pareto1.kurtosis,"\nbase.dists.pareto1.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a Pareto (Type I) distribution.\n"
base.dists.pareto1.logcdf,"\nbase.dists.pareto1.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n"
base.dists.pareto1.logcdf.factory,"\nbase.dists.pareto1.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n"
base.dists.pareto1.logpdf,"\nbase.dists.pareto1.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n"
base.dists.pareto1.logpdf.factory,"\nbase.dists.pareto1.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n"
base.dists.pareto1.mean,"\nbase.dists.pareto1.mean( α:number, β:number )\n Returns the expected value of a Pareto (Type I) distribution.\n"
base.dists.pareto1.median,"\nbase.dists.pareto1.median( α:number, β:number )\n Returns the median of a Pareto (Type I) distribution.\n"
base.dists.pareto1.mode,"\nbase.dists.pareto1.mode( α:number, β:number )\n Returns the mode of a Pareto (Type I) distribution.\n"
base.dists.pareto1.Pareto1,"\nbase.dists.pareto1.Pareto1( [α:number, β:number] )\n Returns a Pareto (Type I) distribution object.\n"
base.dists.pareto1.pdf,"\nbase.dists.pareto1.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n"
base.dists.pareto1.pdf.factory,"\nbase.dists.pareto1.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n"
base.dists.pareto1.quantile,"\nbase.dists.pareto1.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a Pareto (Type I) distribution with\n shape parameter `α` and scale parameter `β` at a probability `p`.\n"
base.dists.pareto1.quantile.factory,"\nbase.dists.pareto1.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n"
base.dists.pareto1.skewness,"\nbase.dists.pareto1.skewness( α:number, β:number )\n Returns the skewness of a Pareto (Type I) distribution.\n"
base.dists.pareto1.stdev,"\nbase.dists.pareto1.stdev( α:number, β:number )\n Returns the standard deviation of a Pareto (Type I) distribution.\n"
base.dists.pareto1.variance,"\nbase.dists.pareto1.variance( α:number, β:number )\n Returns the variance of a Pareto (Type I) distribution.\n"
base.dists.poisson.cdf,"\nbase.dists.poisson.cdf( x:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n"
base.dists.poisson.cdf.factory,"\nbase.dists.poisson.cdf.factory( λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n"
base.dists.poisson.entropy,"\nbase.dists.poisson.entropy( λ:number )\n Returns the entropy of a Poisson distribution.\n"
base.dists.poisson.kurtosis,"\nbase.dists.poisson.kurtosis( λ:number )\n Returns the excess kurtosis of a Poisson distribution.\n"
base.dists.poisson.logpmf,"\nbase.dists.poisson.logpmf( x:number, λ:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n Poisson distribution with mean parameter `λ` at a value `x`.\n"
base.dists.poisson.logpmf.factory,"\nbase.dists.poisson.logpmf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n"
base.dists.poisson.mean,"\nbase.dists.poisson.mean( λ:number )\n Returns the expected value of a Poisson distribution.\n"
base.dists.poisson.median,"\nbase.dists.poisson.median( λ:number )\n Returns the median of a Poisson distribution.\n"
base.dists.poisson.mgf,"\nbase.dists.poisson.mgf( x:number, λ:number )\n Evaluates the moment-generating function (MGF) for a Poisson distribution\n with mean parameter `λ` at a value `x`.\n"
base.dists.poisson.mgf.factory,"\nbase.dists.poisson.mgf.factory( λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n"
base.dists.poisson.mode,"\nbase.dists.poisson.mode( λ:number )\n Returns the mode of a Poisson distribution.\n"
base.dists.poisson.pmf,"\nbase.dists.poisson.pmf( x:number, λ:number )\n Evaluates the probability mass function (PMF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n"
base.dists.poisson.pmf.factory,"\nbase.dists.poisson.pmf.factory( λ:number )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n"
base.dists.poisson.Poisson,"\nbase.dists.poisson.Poisson( [λ:number] )\n Returns a Poisson distribution object.\n"
base.dists.poisson.quantile,"\nbase.dists.poisson.quantile( p:number, λ:number )\n Evaluates the quantile function for a Poisson distribution with mean\n parameter `λ` at a probability `p`.\n"
base.dists.poisson.quantile.factory,"\nbase.dists.poisson.quantile.factory( λ:number )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n"
base.dists.poisson.skewness,"\nbase.dists.poisson.skewness( λ:number )\n Returns the skewness of a Poisson distribution.\n"
base.dists.poisson.stdev,"\nbase.dists.poisson.stdev( λ:number )\n Returns the standard deviation of a Poisson distribution.\n"
base.dists.poisson.variance,"\nbase.dists.poisson.variance( λ:number )\n Returns the variance of a Poisson distribution.\n"
base.dists.rayleigh.cdf,"\nbase.dists.rayleigh.cdf( x:number, sigma:number )\n Evaluates the cumulative distribution function (CDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n"
base.dists.rayleigh.cdf.factory,"\nbase.dists.rayleigh.cdf.factory( sigma:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n"
base.dists.rayleigh.entropy,"\nbase.dists.rayleigh.entropy( σ:number )\n Returns the differential entropy of a Rayleigh distribution.\n"
base.dists.rayleigh.kurtosis,"\nbase.dists.rayleigh.kurtosis( σ:number )\n Returns the excess kurtosis of a Rayleigh distribution.\n"
base.dists.rayleigh.logcdf,"\nbase.dists.rayleigh.logcdf( x:number, sigma:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n"
base.dists.rayleigh.logcdf.factory,"\nbase.dists.rayleigh.logcdf.factory( sigma:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n"
base.dists.rayleigh.logpdf,"\nbase.dists.rayleigh.logpdf( x:number, sigma:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n"
base.dists.rayleigh.logpdf.factory,"\nbase.dists.rayleigh.logpdf.factory( sigma:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n"
base.dists.rayleigh.mean,"\nbase.dists.rayleigh.mean( σ:number )\n Returns the expected value of a Rayleigh distribution.\n"
base.dists.rayleigh.median,"\nbase.dists.rayleigh.median( σ:number )\n Returns the median of a Rayleigh distribution.\n"
base.dists.rayleigh.mgf,"\nbase.dists.rayleigh.mgf( t:number, sigma:number )\n Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n with scale parameter `sigma` at a value `t`.\n"
base.dists.rayleigh.mgf.factory,"\nbase.dists.rayleigh.mgf.factory( sigma:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n"
base.dists.rayleigh.mode,"\nbase.dists.rayleigh.mode( σ:number )\n Returns the mode of a Rayleigh distribution.\n"
base.dists.rayleigh.pdf,"\nbase.dists.rayleigh.pdf( x:number, sigma:number )\n Evaluates the probability density function (PDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n"
base.dists.rayleigh.pdf.factory,"\nbase.dists.rayleigh.pdf.factory( sigma:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n"
base.dists.rayleigh.quantile,"\nbase.dists.rayleigh.quantile( p:number, sigma:number )\n Evaluates the quantile function for a Rayleigh distribution with scale\n parameter `sigma` at a probability `p`.\n"
base.dists.rayleigh.quantile.factory,"\nbase.dists.rayleigh.quantile.factory( sigma:number )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n"
base.dists.rayleigh.Rayleigh,"\nbase.dists.rayleigh.Rayleigh( [σ:number] )\n Returns a Rayleigh distribution object.\n"
base.dists.rayleigh.skewness,"\nbase.dists.rayleigh.skewness( σ:number )\n Returns the skewness of a Rayleigh distribution.\n"
base.dists.rayleigh.stdev,"\nbase.dists.rayleigh.stdev( σ:number )\n Returns the standard deviation of a Rayleigh distribution.\n"
base.dists.rayleigh.variance,"\nbase.dists.rayleigh.variance( σ:number )\n Returns the variance of a Rayleigh distribution.\n"
base.dists.signrank.cdf,"\nbase.dists.signrank.cdf( x:number, n:integer )\n Evaluates the cumulative distribution function (CDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n"
base.dists.signrank.cdf.factory,"\nbase.dists.signrank.cdf.factory( n:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n"
base.dists.signrank.pdf,"\nbase.dists.signrank.pdf( x:number, n:integer )\n Evaluates the probability density function (PDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n"
base.dists.signrank.pdf.factory,"\nbase.dists.signrank.pdf.factory( n:integer )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n"
base.dists.signrank.quantile,"\nbase.dists.signrank.quantile( p:number, n:integer )\n Evaluates the quantile function for the Wilcoxon signed rank test statistic\n with `n` observations at a probability `p`.\n"
base.dists.signrank.quantile.factory,"\nbase.dists.signrank.quantile.factory( n:integer )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n"
base.dists.studentizedRange.cdf,"\nbase.dists.studentizedRange.cdf( x:number, r:number, v:number[, \n nranges:integer] )\n Evaluates the cumulative distribution function (CDF) of a studentized range\n distribution.\n"
base.dists.studentizedRange.cdf.factory,"\nbase.dists.studentizedRange.cdf.factory( r:number, v:number[, nranges:integer] )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a studentized range distribution.\n"
base.dists.studentizedRange.quantile,"\nbase.dists.studentizedRange.quantile( p:number, r:number, v:number[, \n nranges:integer] )\n Evaluates the quantile function for a studentized range distribution.\n"
base.dists.studentizedRange.quantile.factory,"\nbase.dists.studentizedRange.quantile.factory( r:number, v:number[, \n nranges:integer] )\n Returns a function for evaluating the quantile function of a studentized\n range distribution.\n"
base.dists.t.cdf,"\nbase.dists.t.cdf( x:number, v:number )\n Evaluates the cumulative distribution function (CDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n"
base.dists.t.cdf.factory,"\nbase.dists.t.cdf.factory( v:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n"
base.dists.t.entropy,"\nbase.dists.t.entropy( v:number )\n Returns the differential entropy of a Student's t distribution.\n"
base.dists.t.kurtosis,"\nbase.dists.t.kurtosis( v:number )\n Returns the excess kurtosis of a Student's t distribution.\n"
base.dists.t.logcdf,"\nbase.dists.t.logcdf( x:number, v:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Student's t distribution with degrees of freedom `v` at a value\n `x`.\n"
base.dists.t.logcdf.factory,"\nbase.dists.t.logcdf.factory( v:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Student's t distribution with degrees of\n freedom `v`.\n"
base.dists.t.logpdf,"\nbase.dists.t.logpdf( x:number, v:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Student's t distribution with degrees of freedom `v` at a value `x`.\n"
base.dists.t.logpdf.factory,"\nbase.dists.t.logpdf.factory( v:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Student's t distribution with degrees of\n freedom `v`.\n"
base.dists.t.mean,"\nbase.dists.t.mean( v:number )\n Returns the expected value of a Student's t distribution.\n"
base.dists.t.median,"\nbase.dists.t.median( v:number )\n Returns the median of a Student's t distribution.\n"
base.dists.t.mode,"\nbase.dists.t.mode( v:number )\n Returns the mode of a Student's t distribution.\n"
base.dists.t.pdf,"\nbase.dists.t.pdf( x:number, v:number )\n Evaluates the probability density function (PDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n"
base.dists.t.pdf.factory,"\nbase.dists.t.pdf.factory( v:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n"
base.dists.t.quantile,"\nbase.dists.t.quantile( p:number, v:number )\n Evaluates the quantile function for a Student's t distribution with degrees\n of freedom `v` at a probability `p`.\n"
base.dists.t.quantile.factory,"\nbase.dists.t.quantile.factory( v:number )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n"
base.dists.t.skewness,"\nbase.dists.t.skewness( v:number )\n Returns the skewness of a Student's t distribution.\n"
base.dists.t.stdev,"\nbase.dists.t.stdev( v:number )\n Returns the standard deviation of a Student's t distribution.\n"
base.dists.t.T,"\nbase.dists.t.T( [v:number] )\n Returns a Student's t distribution object.\n"
base.dists.t.variance,"\nbase.dists.t.variance( v:number )\n Returns the variance of a Student's t distribution.\n"
base.dists.triangular.cdf,"\nbase.dists.triangular.cdf( x:number, a:number, b:number, c:number )\n Evaluates the cumulative distribution function (CDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n"
base.dists.triangular.cdf.factory,"\nbase.dists.triangular.cdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n"
base.dists.triangular.entropy,"\nbase.dists.triangular.entropy( a:number, b:number, c:number )\n Returns the differential entropy of a triangular distribution (in nats).\n"
base.dists.triangular.kurtosis,"\nbase.dists.triangular.kurtosis( a:number, b:number, c:number )\n Returns the excess kurtosis of a triangular distribution.\n"
base.dists.triangular.logcdf,"\nbase.dists.triangular.logcdf( x:number, a:number, b:number, c:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a triangular distribution with minimum support `a`, maximum\n support `b`, and mode `c` at a value `x`.\n"
base.dists.triangular.logcdf.factory,"\nbase.dists.triangular.logcdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n"
base.dists.triangular.logpdf,"\nbase.dists.triangular.logpdf( x:number, a:number, b:number, c:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c` at a value `x`.\n"
base.dists.triangular.logpdf.factory,"\nbase.dists.triangular.logpdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n"
base.dists.triangular.mean,"\nbase.dists.triangular.mean( a:number, b:number, c:number )\n Returns the expected value of a triangular distribution.\n"
base.dists.triangular.median,"\nbase.dists.triangular.median( a:number, b:number, c:number )\n Returns the median of a triangular distribution.\n"
base.dists.triangular.mgf,"\nbase.dists.triangular.mgf( t:number, a:number, b:number, c:number )\n Evaluates the moment-generating function (MGF) for a triangular distribution\n with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n"
base.dists.triangular.mgf.factory,"\nbase.dists.triangular.mgf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n"
base.dists.triangular.mode,"\nbase.dists.triangular.mode( a:number, b:number, c:number )\n Returns the mode of a triangular distribution.\n"
base.dists.triangular.pdf,"\nbase.dists.triangular.pdf( x:number, a:number, b:number, c:number )\n Evaluates the probability density function (PDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n"
base.dists.triangular.pdf.factory,"\nbase.dists.triangular.pdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n"
base.dists.triangular.quantile,"\nbase.dists.triangular.quantile( p:number, a:number, b:number, c:number )\n Evaluates the quantile function for a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c` at a value `x`.\n"
base.dists.triangular.quantile.factory,"\nbase.dists.triangular.quantile.factory( a:number, b:number, c:number )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n"
base.dists.triangular.skewness,"\nbase.dists.triangular.skewness( a:number, b:number, c:number )\n Returns the skewness of a triangular distribution.\n"
base.dists.triangular.stdev,"\nbase.dists.triangular.stdev( a:number, b:number, c:number )\n Returns the standard deviation of a triangular distribution.\n"
base.dists.triangular.Triangular,"\nbase.dists.triangular.Triangular( [a:number, b:number, c:number] )\n Returns a triangular distribution object.\n"
base.dists.triangular.variance,"\nbase.dists.triangular.variance( a:number, b:number, c:number )\n Returns the variance of a triangular distribution.\n"
base.dists.uniform.cdf,"\nbase.dists.uniform.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n"
base.dists.uniform.cdf.factory,"\nbase.dists.uniform.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n"
base.dists.uniform.entropy,"\nbase.dists.uniform.entropy( a:number, b:number )\n Returns the differential entropy of a uniform distribution.\n"
base.dists.uniform.kurtosis,"\nbase.dists.uniform.kurtosis( a:number, b:number )\n Returns the excess kurtosis of a uniform distribution.\n"
base.dists.uniform.logcdf,"\nbase.dists.uniform.logcdf( x:number, a:number, b:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n"
base.dists.uniform.logcdf.factory,"\nbase.dists.uniform.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n"
base.dists.uniform.logpdf,"\nbase.dists.uniform.logpdf( x:number, a:number, b:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n"
base.dists.uniform.logpdf.factory,"\nbase.dists.uniform.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n"
base.dists.uniform.mean,"\nbase.dists.uniform.mean( a:number, b:number )\n Returns the expected value of a uniform distribution.\n"
base.dists.uniform.median,"\nbase.dists.uniform.median( a:number, b:number )\n Returns the median of a uniform distribution.\n"
base.dists.uniform.mgf,"\nbase.dists.uniform.mgf( t:number, a:number, b:number )\n Evaluates the moment-generating function (MGF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n"
base.dists.uniform.mgf.factory,"\nbase.dists.uniform.mgf.factory( a:number, b:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n"
base.dists.uniform.pdf,"\nbase.dists.uniform.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for a uniform distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n"
base.dists.uniform.pdf.factory,"\nbase.dists.uniform.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n"
base.dists.uniform.quantile,"\nbase.dists.uniform.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for a uniform distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n"
base.dists.uniform.quantile.factory,"\nbase.dists.uniform.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n"
base.dists.uniform.skewness,"\nbase.dists.uniform.skewness( a:number, b:number )\n Returns the skewness of a uniform distribution.\n"
base.dists.uniform.stdev,"\nbase.dists.uniform.stdev( a:number, b:number )\n Returns the standard deviation of a uniform distribution.\n"
base.dists.uniform.Uniform,"\nbase.dists.uniform.Uniform( [a:number, b:number] )\n Returns a uniform distribution object.\n"
base.dists.uniform.variance,"\nbase.dists.uniform.variance( a:number, b:number )\n Returns the variance of a uniform distribution.\n"
base.dists.weibull.cdf,"\nbase.dists.weibull.cdf( x:number, k:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for a Weibull\n distribution with shape parameter `k` and scale parameter `λ` at a value\n `x`.\n"
base.dists.weibull.cdf.factory,"\nbase.dists.weibull.cdf.factory( k:number, λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n"
base.dists.weibull.entropy,"\nbase.dists.weibull.entropy( k:number, λ:number )\n Returns the differential entropy of a Weibull distribution (in nats).\n"
base.dists.weibull.kurtosis,"\nbase.dists.weibull.kurtosis( k:number, λ:number )\n Returns the excess kurtosis of a Weibull distribution.\n"
base.dists.weibull.logcdf,"\nbase.dists.weibull.logcdf( x:number, k:number, λ:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n"
base.dists.weibull.logcdf.factory,"\nbase.dists.weibull.logcdf.factory( k:number, λ:number)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n"
base.dists.weibull.logpdf,"\nbase.dists.weibull.logpdf( x:number, k:number, λ:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n"
base.dists.weibull.logpdf.factory,"\nbase.dists.weibull.logpdf.factory( k:number, λ:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n"
base.dists.weibull.mean,"\nbase.dists.weibull.mean( k:number, λ:number )\n Returns the expected value of a Weibull distribution.\n"
base.dists.weibull.median,"\nbase.dists.weibull.median( k:number, λ:number )\n Returns the median of a Weibull distribution.\n"
base.dists.weibull.mgf,"\nbase.dists.weibull.mgf( x:number, k:number, λ:number )\n Evaluates the moment-generating function (MGF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `t`.\n"
base.dists.weibull.mgf.factory,"\nbase.dists.weibull.mgf.factory( k:number, λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n"
base.dists.weibull.mode,"\nbase.dists.weibull.mode( k:number, λ:number )\n Returns the mode of a Weibull distribution.\n"
base.dists.weibull.pdf,"\nbase.dists.weibull.pdf( x:number, k:number, λ:number )\n Evaluates the probability density function (PDF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `x`.\n"
base.dists.weibull.pdf.factory,"\nbase.dists.weibull.pdf.factory( k:number, λ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n"
base.dists.weibull.quantile,"\nbase.dists.weibull.quantile( p:number, k:number, λ:number )\n Evaluates the quantile function for a Weibull distribution with scale\n parameter `k` and shape parameter `λ` at a probability `p`.\n"
base.dists.weibull.quantile.factory,"\nbase.dists.weibull.quantile.factory( k:number, λ:number )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n"
base.dists.weibull.skewness,"\nbase.dists.weibull.skewness( k:number, λ:number )\n Returns the skewness of a Weibull distribution.\n"
base.dists.weibull.stdev,"\nbase.dists.weibull.stdev( k:number, λ:number )\n Returns the standard deviation of a Weibull distribution.\n"
base.dists.weibull.variance,"\nbase.dists.weibull.variance( k:number, λ:number )\n Returns the variance of a Weibull distribution.\n"
base.dists.weibull.Weibull,"\nbase.dists.weibull.Weibull( [k:number, λ:number] )\n Returns a Weibull distribution object.\n"
base.ellipe,"\nbase.ellipe( m:number )\n Computes the complete elliptic integral of the second kind.\n"
base.ellipj,"\nbase.ellipj( u:number, m:number )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am.\n"
base.ellipj.assign,"\nbase.ellipj.assign( u:number, m:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n"
base.ellipj.sn,"\nbase.ellipj.sn( u:number, m:number )\n Computes the Jacobi elliptic function sn.\n"
base.ellipj.cn,"\nbase.ellipj.cn( u:number, m:number )\n Computes the Jacobi elliptic functions cn.\n"
base.ellipj.dn,"\nbase.ellipj.dn( u:number, m:number )\n Computes the Jacobi elliptic function dn.\n"
base.ellipj.am,"\nbase.ellipj.am( u:number, m:number )\n Computes the Jacobi amplitude am.\n"
base.ellipk,"\nbase.ellipk( m:number )\n Computes the complete elliptic integral of the first kind.\n"
base.endsWith,"\nbase.endsWith( str:string, search:string, len:integer )\n Tests if a string ends with the characters of another string.\n"
base.epsdiff,"\nbase.epsdiff( x:number, y:number[, scale:string|Function] )\n Computes the relative difference of two real numbers in units of double-\n precision floating-point epsilon.\n"
base.erf,"\nbase.erf( x:number )\n Evaluates the error function.\n"
base.erfc,"\nbase.erfc( x:number )\n Evaluates the complementary error function.\n"
base.erfcinv,"\nbase.erfcinv( x:number )\n Evaluates the inverse complementary error function.\n"
base.erfcx,"\nbase.erfcx( x:number )\n Evaluates the scaled complementary error function.\n"
base.erfinv,"\nbase.erfinv( x:number )\n Evaluates the inverse error function.\n"
base.eta,"\nbase.eta( s:number )\n Evaluates the Dirichlet eta function for a double-precision\n floating-point number `s`.\n"
base.evalpoly,"\nbase.evalpoly( c:Array<number>, x:number )\n Evaluates a polynomial using double-precision floating-point arithmetic.\n"
base.evalpoly.factory,"\nbase.evalpoly.factory( c:Array<number> )\n Returns a function for evaluating a polynomial using double-precision\n floating-point arithmetic.\n"
base.evalrational,"\nbase.evalrational( P:Array<number>, Q:Array<number>, x:number )\n Evaluates a rational function using double-precision floating-point\n arithmetic.\n"
base.evalrational.factory,"\nbase.evalrational.factory( P:Array<number>, Q:Array<number> )\n Returns a function for evaluating a rational function using double-precision\n floating-point arithmetic.\n"
base.exp,"\nbase.exp( x:number )\n Evaluates the natural exponential function.\n"
base.exp2,"\nbase.exp2( x:number )\n Evaluates the base 2 exponential function.\n"
base.exp10,"\nbase.exp10( x:number )\n Evaluates the base 10 exponential function.\n"
base.expit,"\nbase.expit( x:number )\n Evaluates the standard logistic function.\n"
base.expm1,"\nbase.expm1( x:number )\n Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n"
base.expm1rel,"\nbase.expm1rel( x:number )\n Relative error exponential.\n"
base.exponent,"\nbase.exponent( x:number )\n Returns an integer corresponding to the unbiased exponent of a double-\n precision floating-point number.\n"
base.exponentf,"\nbase.exponentf( x:float )\n Returns an integer corresponding to the unbiased exponent of a single-\n precision floating-point number.\n"
base.factorial,"\nbase.factorial( x:number )\n Evaluates the factorial of `x`.\n"
base.factorial2,"\nbase.factorial2( n:number )\n Evaluates the double factorial of `n`.\n"
base.factorialln,"\nbase.factorialln( x:number )\n Evaluates the natural logarithm of the factorial of `x`.\n"
base.fallingFactorial,"\nbase.fallingFactorial( x:number, n:integer )\n Computes the falling factorial of `x` and `n`.\n"
base.fibonacci,"\nbase.fibonacci( n:integer )\n Computes the nth Fibonacci number.\n"
base.fibonacciIndex,"\nbase.fibonacciIndex( F:integer )\n Computes the Fibonacci number index.\n"
base.fibpoly,"\nbase.fibpoly( n:integer, x:number )\n Evaluates a Fibonacci polynomial.\n"
base.fibpoly.factory,"\nbase.fibpoly.factory( n:integer )\n Returns a function for evaluating a Fibonacci polynomial.\n"
base.firstCodePoint,"\nbase.firstCodePoint( str:string, n:integer )\n Returns the first `n` Unicode code points of a string.\n"
base.firstCodeUnit,"\nbase.firstCodeUnit( str:string, n:integer )\n Returns the first `n` UTF-16 code units of a string.\n"
base.firstGraphemeCluster,"\nbase.firstGraphemeCluster( str:string, n:integer )\n Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n"
base.flipsign,"\nbase.flipsign( x:number, y:number )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n"
base.flipsignf,"\nbase.flipsignf( x:number, y:number )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n"
base.float32ToInt32,"\nbase.float32ToInt32( x:float )\n Converts a single-precision floating-point number to a signed 32-bit\n integer.\n"
base.float32ToUint32,"\nbase.float32ToUint32( x:float )\n Converts a single-precision floating-point number to a unsigned 32-bit\n integer.\n"
base.float64ToFloat32,"\nbase.float64ToFloat32( x:number )\n Converts a double-precision floating-point number to the nearest single-\n precision floating-point number.\n"
base.float64ToInt32,"\nbase.float64ToInt32( x:number )\n Converts a double-precision floating-point number to a signed 32-bit\n integer.\n"
base.float64ToInt64Bytes,"\nbase.float64ToInt64Bytes( x:integer )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness).\n"
base.float64ToInt64Bytes.assign,"\nbase.float64ToInt64Bytes.assign( x:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n"
base.float64ToUint32,"\nbase.float64ToUint32( x:number )\n Converts a double-precision floating-point number to a unsigned 32-bit\n integer.\n"
base.floor,"\nbase.floor( x:number )\n Rounds a double-precision floating-point number toward negative infinity.\n"
base.floor2,"\nbase.floor2( x:number )\n Rounds a numeric value to the nearest power of two toward negative infinity.\n"
base.floor10,"\nbase.floor10( x:number )\n Rounds a numeric value to the nearest power of ten toward negative infinity.\n"
base.floorb,"\nbase.floorb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward negative\n infinity.\n"
base.floorf,"\nbase.floorf( x:number )\n Rounds a single-precision floating-point number toward negative infinity.\n"
base.floorn,"\nbase.floorn( x:number, n:integer )\n Rounds a double-precision floating-point number to the nearest multiple of\n `10^n` toward negative infinity.\n"
base.floorsd,"\nbase.floorsd( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest number toward negative infinity with\n `n` significant figures.\n"
base.forEachChar,"\nbase.forEachChar( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each UTF-16 code unit in a string.\n"
base.forEachCodePoint,"\nbase.forEachCodePoint( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each Unicode code point in a string.\n"
base.forEachCodePointRight,"\nbase.forEachCodePointRight( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each Unicode code point in a string, iterating from\n right to left.\n"
base.forEachGraphemeCluster,"\nbase.forEachGraphemeCluster( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each grapheme cluster (i.e., user-perceived\n character) in a string.\n"
base.forEachRight,"\nbase.forEachRight( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each UTF-16 code unit in a string, iterating from\n right to left.\n"