diff --git a/lib/node_modules/@stdlib/blas/ext/base/README.md b/lib/node_modules/@stdlib/blas/ext/base/README.md
index 93833964c9e6..4187e545aebe 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/README.md
+++ b/lib/node_modules/@stdlib/blas/ext/base/README.md
@@ -87,8 +87,8 @@ var ns = extblas;
 -   <span class="signature">[`dsum( N, x, strideX )`][@stdlib/blas/ext/base/dsum]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements.</span>
 -   <span class="signature">[`dsumkbn( N, x, strideX )`][@stdlib/blas/ext/base/dsumkbn]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements using an improved Kahan–Babuška algorithm.</span>
 -   <span class="signature">[`dsumkbn2( N, x, strideX )`][@stdlib/blas/ext/base/dsumkbn2]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm.</span>
--   <span class="signature">[`dsumors( N, x, stride )`][@stdlib/blas/ext/base/dsumors]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements using ordinary recursive summation.</span>
--   <span class="signature">[`dsumpw( N, x, stride )`][@stdlib/blas/ext/base/dsumpw]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements using pairwise summation.</span>
+-   <span class="signature">[`dsumors( N, x, strideX )`][@stdlib/blas/ext/base/dsumors]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements using ordinary recursive summation.</span>
+-   <span class="signature">[`dsumpw( N, x, strideX )`][@stdlib/blas/ext/base/dsumpw]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements using pairwise summation.</span>
 -   <span class="signature">[`gapx( N, alpha, x, stride )`][@stdlib/blas/ext/base/gapx]</span><span class="delimiter">: </span><span class="description">add a constant to each element in a strided array.</span>
 -   <span class="signature">[`gapxsum( N, alpha, x, stride )`][@stdlib/blas/ext/base/gapxsum]</span><span class="delimiter">: </span><span class="description">add a constant to each strided array element and compute the sum.</span>
 -   <span class="signature">[`gapxsumkbn( N, alpha, x, strideX )`][@stdlib/blas/ext/base/gapxsumkbn]</span><span class="delimiter">: </span><span class="description">add a scalar constant to each strided array element and compute the sum using an improved Kahan–Babuška algorithm.</span>
@@ -104,11 +104,11 @@ var ns = extblas;
 -   <span class="signature">[`gfillBy( N, x, stride, clbk[, thisArg] )`][@stdlib/blas/ext/base/gfill-by]</span><span class="delimiter">: </span><span class="description">fill a strided array according to a provided callback function.</span>
 -   <span class="signature">[`gfill( N, alpha, x, stride )`][@stdlib/blas/ext/base/gfill]</span><span class="delimiter">: </span><span class="description">fill a strided array with a specified scalar constant.</span>
 -   <span class="signature">[`gnannsumkbn( N, x, strideX, out, strideOut )`][@stdlib/blas/ext/base/gnannsumkbn]</span><span class="delimiter">: </span><span class="description">calculate the sum of strided array elements, ignoring `NaN` values and using an improved Kahan–Babuška algorithm.</span>
--   <span class="signature">[`gnansum( N, x, stride )`][@stdlib/blas/ext/base/gnansum]</span><span class="delimiter">: </span><span class="description">calculate the sum of strided array elements, ignoring `NaN` values.</span>
--   <span class="signature">[`gnansumkbn( N, x, stride )`][@stdlib/blas/ext/base/gnansumkbn]</span><span class="delimiter">: </span><span class="description">calculate the sum of strided array elements, ignoring `NaN` values and using an improved Kahan–Babuška algorithm.</span>
--   <span class="signature">[`gnansumkbn2( N, x, stride )`][@stdlib/blas/ext/base/gnansumkbn2]</span><span class="delimiter">: </span><span class="description">calculate the sum of strided array elements, ignoring `NaN` values and using a second-order iterative Kahan–Babuška algorithm.</span>
--   <span class="signature">[`gnansumors( N, x, stride )`][@stdlib/blas/ext/base/gnansumors]</span><span class="delimiter">: </span><span class="description">calculate the sum of strided array elements, ignoring `NaN` values and using ordinary recursive summation.</span>
--   <span class="signature">[`gnansumpw( N, x, stride )`][@stdlib/blas/ext/base/gnansumpw]</span><span class="delimiter">: </span><span class="description">calculate the sum of strided array elements, ignoring `NaN` values and using pairwise summation.</span>
+-   <span class="signature">[`gnansum( N, x, strideX )`][@stdlib/blas/ext/base/gnansum]</span><span class="delimiter">: </span><span class="description">calculate the sum of strided array elements, ignoring `NaN` values.</span>
+-   <span class="signature">[`gnansumkbn( N, x, strideX )`][@stdlib/blas/ext/base/gnansumkbn]</span><span class="delimiter">: </span><span class="description">calculate the sum of strided array elements, ignoring `NaN` values and using an improved Kahan–Babuška algorithm.</span>
+-   <span class="signature">[`gnansumkbn2( N, x, strideX )`][@stdlib/blas/ext/base/gnansumkbn2]</span><span class="delimiter">: </span><span class="description">calculate the sum of strided array elements, ignoring `NaN` values and using a second-order iterative Kahan–Babuška algorithm.</span>
+-   <span class="signature">[`gnansumors( N, x, strideX )`][@stdlib/blas/ext/base/gnansumors]</span><span class="delimiter">: </span><span class="description">calculate the sum of strided array elements, ignoring `NaN` values and using ordinary recursive summation.</span>
+-   <span class="signature">[`gnansumpw( N, x, strideX )`][@stdlib/blas/ext/base/gnansumpw]</span><span class="delimiter">: </span><span class="description">calculate the sum of strided array elements, ignoring `NaN` values and using pairwise summation.</span>
 -   <span class="signature">[`grev( N, x, stride )`][@stdlib/blas/ext/base/grev]</span><span class="delimiter">: </span><span class="description">reverse a strided array in-place.</span>
 -   <span class="signature">[`gsort2hp( N, order, x, strideX, y, strideY )`][@stdlib/blas/ext/base/gsort2hp]</span><span class="delimiter">: </span><span class="description">simultaneously sort two strided arrays based on the sort order of the first array using heapsort.</span>
 -   <span class="signature">[`gsort2ins( N, order, x, strideX, y, strideY )`][@stdlib/blas/ext/base/gsort2ins]</span><span class="delimiter">: </span><span class="description">simultaneously sort two strided arrays based on the sort order of the first array using insertion sort.</span>
diff --git a/lib/node_modules/@stdlib/stats/base/README.md b/lib/node_modules/@stdlib/stats/base/README.md
index a441b6698bd7..3754b2b20ed5 100644
--- a/lib/node_modules/@stdlib/stats/base/README.md
+++ b/lib/node_modules/@stdlib/stats/base/README.md
@@ -81,7 +81,7 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`dmeanstdevpn( N, correction, x, strideX, out, strideOut )`][@stdlib/stats/base/dmeanstdevpn]</span><span class="delimiter">: </span><span class="description">calculate the mean and standard deviation of a double-precision floating-point strided array using a two-pass algorithm.</span>
 -   <span class="signature">[`dmeanvar( N, correction, x, strideX, out, strideOut )`][@stdlib/stats/base/dmeanvar]</span><span class="delimiter">: </span><span class="description">calculate the mean and variance of a double-precision floating-point strided array.</span>
 -   <span class="signature">[`dmeanvarpn( N, correction, x, strideX, out, strideOut )`][@stdlib/stats/base/dmeanvarpn]</span><span class="delimiter">: </span><span class="description">calculate the mean and variance of a double-precision floating-point strided array using a two-pass algorithm.</span>
--   <span class="signature">[`dmeanwd( N, x, stride )`][@stdlib/stats/base/dmeanwd]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using Welford's algorithm.</span>
+-   <span class="signature">[`dmeanwd( N, x, strideX )`][@stdlib/stats/base/dmeanwd]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using Welford's algorithm.</span>
 -   <span class="signature">[`dmediansorted( N, x, strideX )`][@stdlib/stats/base/dmediansorted]</span><span class="delimiter">: </span><span class="description">calculate the median value of a sorted double-precision floating-point strided array.</span>
 -   <span class="signature">[`dmidrange( N, x, strideX )`][@stdlib/stats/base/dmidrange]</span><span class="delimiter">: </span><span class="description">calculate the mid-range of a double-precision floating-point strided array.</span>
 -   <span class="signature">[`dmin( N, x, strideX )`][@stdlib/stats/base/dmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a double-precision floating-point strided array.</span>
@@ -132,11 +132,11 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`dsnanmeanpn( N, x, stride )`][@stdlib/stats/base/dsnanmeanpn]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values, using a two-pass error correction algorithm with extended accumulation, and returning an extended precision result.</span>
 -   <span class="signature">[`dsnanmeanwd( N, x, stride )`][@stdlib/stats/base/dsnanmeanwd]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values, using Welford's algorithm with extended accumulation, and returning an extended precision result.</span>
 -   <span class="signature">[`dstdev( N, correction, x, stride )`][@stdlib/stats/base/dstdev]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array.</span>
--   <span class="signature">[`dstdevch( N, correction, x, stride )`][@stdlib/stats/base/dstdevch]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array using a one-pass trial mean algorithm.</span>
+-   <span class="signature">[`dstdevch( N, correction, x, strideX )`][@stdlib/stats/base/dstdevch]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array using a one-pass trial mean algorithm.</span>
 -   <span class="signature">[`dstdevpn( N, correction, x, stride )`][@stdlib/stats/base/dstdevpn]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array using a two-pass algorithm.</span>
--   <span class="signature">[`dstdevtk( N, correction, x, stride )`][@stdlib/stats/base/dstdevtk]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array using a one-pass textbook algorithm.</span>
--   <span class="signature">[`dstdevwd( N, correction, x, stride )`][@stdlib/stats/base/dstdevwd]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array using Welford's algorithm.</span>
--   <span class="signature">[`dstdevyc( N, correction, x, stride )`][@stdlib/stats/base/dstdevyc]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer.</span>
+-   <span class="signature">[`dstdevtk( N, correction, x, strideX )`][@stdlib/stats/base/dstdevtk]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array using a one-pass textbook algorithm.</span>
+-   <span class="signature">[`dstdevwd( N, correction, x, strideX )`][@stdlib/stats/base/dstdevwd]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array using Welford's algorithm.</span>
+-   <span class="signature">[`dstdevyc( N, correction, x, strideX )`][@stdlib/stats/base/dstdevyc]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer.</span>
 -   <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>