docs: update namespace table of contents

PR-URL: #4520

Reviewed-by: Philipp Burckhardt <[email protected]>
Signed-off-by: stdlib-bot <[email protected]>

Author: stdlib-bot

Diff for: lib/node_modules/@stdlib/stats/base/README.md

@@ -96,7 +96,7 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`dnanmeanors( N, x, stride )`][@stdlib/stats/base/dnanmeanors]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using ordinary recursive summation.</span>
 -   <span class="signature">[`dnanmeanpn( N, x, stride )`][@stdlib/stats/base/dnanmeanpn]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using a two-pass error correction algorithm.</span>
 -   <span class="signature">[`dnanmeanpw( N, x, stride )`][@stdlib/stats/base/dnanmeanpw]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using pairwise summation.</span>
--   <span class="signature">[`dnanmeanwd( N, x, stride )`][@stdlib/stats/base/dnanmeanwd]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array, using Welford's algorithm and ignoring `NaN` values.</span>
+-   <span class="signature">[`dnanmeanwd( N, x, strideX )`][@stdlib/stats/base/dnanmeanwd]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array, using Welford's algorithm and ignoring `NaN` values.</span>
 -   <span class="signature">[`dnanmin( N, x, strideX )`][@stdlib/stats/base/dnanmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a double-precision floating-point strided array, ignoring `NaN` values.</span>
 -   <span class="signature">[`dnanminabs( N, x, strideX )`][@stdlib/stats/base/dnanminabs]</span><span class="delimiter">: </span><span class="description">calculate the minimum absolute value of a double-precision floating-point strided array, ignoring `NaN` values.</span>
 -   <span class="signature">[`dnanmskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/dnanmskmax]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a double-precision floating-point strided array according to a mask, ignoring `NaN` values.</span>
@@ -217,11 +217,11 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`smeanpn( N, x, stride )`][@stdlib/stats/base/smeanpn]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm.</span>
 -   <span class="signature">[`smeanpw( N, x, stride )`][@stdlib/stats/base/smeanpw]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using pairwise summation.</span>
 -   <span class="signature">[`smeanwd( N, x, stride )`][@stdlib/stats/base/smeanwd]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm.</span>
--   <span class="signature">[`smediansorted( N, x, stride )`][@stdlib/stats/base/smediansorted]</span><span class="delimiter">: </span><span class="description">calculate the median value of a sorted single-precision floating-point strided array.</span>
+-   <span class="signature">[`smediansorted( N, x, strideX )`][@stdlib/stats/base/smediansorted]</span><span class="delimiter">: </span><span class="description">calculate the median value of a sorted single-precision floating-point strided array.</span>
 -   <span class="signature">[`smidrange( N, x, strideX )`][@stdlib/stats/base/smidrange]</span><span class="delimiter">: </span><span class="description">calculate the mid-range of a single-precision floating-point strided array.</span>
 -   <span class="signature">[`smin( N, x, strideX )`][@stdlib/stats/base/smin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a single-precision floating-point strided array.</span>
 -   <span class="signature">[`sminabs( N, x, strideX )`][@stdlib/stats/base/sminabs]</span><span class="delimiter">: </span><span class="description">calculate the minimum absolute value of a single-precision floating-point strided array.</span>
--   <span class="signature">[`sminsorted( N, x, stride )`][@stdlib/stats/base/sminsorted]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a sorted single-precision floating-point strided array.</span>
+-   <span class="signature">[`sminsorted( N, x, strideX )`][@stdlib/stats/base/sminsorted]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a sorted single-precision floating-point strided array.</span>
 -   <span class="signature">[`smskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/smskmax]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a single-precision floating-point strided array according to a mask.</span>
 -   <span class="signature">[`smskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/smskmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a single-precision floating-point strided array according to a mask.</span>
 -   <span class="signature">[`smskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/smskrange]</span><span class="delimiter">: </span><span class="description">calculate the range of a single-precision floating-point strided array according to a mask.</span>