diff --git a/lib/node_modules/@stdlib/stats/base/README.md b/lib/node_modules/@stdlib/stats/base/README.md
index 4c24763dbda5..a441b6698bd7 100644
--- a/lib/node_modules/@stdlib/stats/base/README.md
+++ b/lib/node_modules/@stdlib/stats/base/README.md
@@ -140,14 +140,14 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`dsvariance( N, correction, x, stride )`][@stdlib/stats/base/dsvariance]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array using extended accumulation and returning an extended precision result.</span>
 -   <span class="signature">[`dsvariancepn( N, correction, x, stride )`][@stdlib/stats/base/dsvariancepn]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array using a two-pass algorithm with extended accumulation and returning an extended precision result.</span>
 -   <span class="signature">[`dvariance( N, correction, x, stride )`][@stdlib/stats/base/dvariance]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array.</span>
--   <span class="signature">[`dvariancech( N, correction, x, stride )`][@stdlib/stats/base/dvariancech]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array using a one-pass trial mean algorithm.</span>
+-   <span class="signature">[`dvariancech( N, correction, x, strideX )`][@stdlib/stats/base/dvariancech]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array using a one-pass trial mean algorithm.</span>
 -   <span class="signature">[`dvariancepn( N, correction, x, stride )`][@stdlib/stats/base/dvariancepn]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array using a two-pass algorithm.</span>
--   <span class="signature">[`dvariancetk( N, correction, x, stride )`][@stdlib/stats/base/dvariancetk]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array using a one-pass textbook algorithm.</span>
--   <span class="signature">[`dvariancewd( N, correction, x, stride )`][@stdlib/stats/base/dvariancewd]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array using Welford's algorithm.</span>
--   <span class="signature">[`dvarianceyc( N, correction, x, stride )`][@stdlib/stats/base/dvarianceyc]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer.</span>
+-   <span class="signature">[`dvariancetk( N, correction, x, strideX )`][@stdlib/stats/base/dvariancetk]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array using a one-pass textbook algorithm.</span>
+-   <span class="signature">[`dvariancewd( N, correction, x, strideX )`][@stdlib/stats/base/dvariancewd]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array using Welford's algorithm.</span>
+-   <span class="signature">[`dvarianceyc( N, correction, x, strideX )`][@stdlib/stats/base/dvarianceyc]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer.</span>
 -   <span class="signature">[`dvarm( N, mean, correction, x, stride )`][@stdlib/stats/base/dvarm]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array provided a known mean.</span>
 -   <span class="signature">[`dvarmpn( N, mean, correction, x, stride )`][@stdlib/stats/base/dvarmpn]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array provided a known mean and using Neely's correction algorithm.</span>
--   <span class="signature">[`dvarmtk( N, mean, correction, x, stride )`][@stdlib/stats/base/dvarmtk]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array provided a known mean and using a one-pass textbook algorithm.</span>
+-   <span class="signature">[`dvarmtk( N, mean, correction, x, strideX )`][@stdlib/stats/base/dvarmtk]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array provided a known mean and using a one-pass textbook algorithm.</span>
 -   <span class="signature">[`maxBy( N, x, stride, clbk[, thisArg] )`][@stdlib/stats/base/max-by]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a strided array via a callback function.</span>
 -   <span class="signature">[`max( N, x, stride )`][@stdlib/stats/base/max]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a strided array.</span>
 -   <span class="signature">[`maxabs( N, x, stride )`][@stdlib/stats/base/maxabs]</span><span class="delimiter">: </span><span class="description">calculate the maximum absolute value of a strided array.</span>
@@ -216,7 +216,7 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`smeanors( N, x, stride )`][@stdlib/stats/base/smeanors]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation.</span>
 -   <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">[`smeanwd( N, x, strideX )`][@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, 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>
@@ -263,9 +263,9 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`stdevwd( N, correction, x, stride )`][@stdlib/stats/base/stdevwd]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a strided array using Welford's algorithm.</span>
 -   <span class="signature">[`stdevyc( N, correction, x, stride )`][@stdlib/stats/base/stdevyc]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a strided array using a one-pass algorithm proposed by Youngs and Cramer.</span>
 -   <span class="signature">[`svariance( N, correction, x, stride )`][@stdlib/stats/base/svariance]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array.</span>
--   <span class="signature">[`svariancech( N, correction, x, stride )`][@stdlib/stats/base/svariancech]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array using a one-pass trial mean algorithm.</span>
+-   <span class="signature">[`svariancech( N, correction, x, strideX )`][@stdlib/stats/base/svariancech]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array using a one-pass trial mean algorithm.</span>
 -   <span class="signature">[`svariancepn( N, correction, x, stride )`][@stdlib/stats/base/svariancepn]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array using a two-pass algorithm.</span>
--   <span class="signature">[`svariancetk( N, correction, x, stride )`][@stdlib/stats/base/svariancetk]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array using a one-pass textbook algorithm.</span>
+-   <span class="signature">[`svariancetk( N, correction, x, strideX )`][@stdlib/stats/base/svariancetk]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array using a one-pass textbook algorithm.</span>
 -   <span class="signature">[`svariancewd( N, correction, x, stride )`][@stdlib/stats/base/svariancewd]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array using Welford's algorithm.</span>
 -   <span class="signature">[`svarianceyc( N, correction, x, stride )`][@stdlib/stats/base/svarianceyc]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer.</span>
 -   <span class="signature">[`variance( N, correction, x, stride )`][@stdlib/stats/base/variance]</span><span class="delimiter">: </span><span class="description">calculate the variance of a strided array.</span>