diff --git a/lib/node_modules/@stdlib/blas/ext/base/README.md b/lib/node_modules/@stdlib/blas/ext/base/README.md
index 6916947f92a2..1b8ca386b627 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/README.md
+++ b/lib/node_modules/@stdlib/blas/ext/base/README.md
@@ -143,7 +143,7 @@ var ns = extblas;
 -   <span class="signature">[`snansum( N, x, stride )`][@stdlib/blas/ext/base/snansum]</span><span class="delimiter">: </span><span class="description">calculate the sum of single-precision floating-point strided array elements, ignoring `NaN` values.</span>
 -   <span class="signature">[`snansumkbn( N, x, stride )`][@stdlib/blas/ext/base/snansumkbn]</span><span class="delimiter">: </span><span class="description">calculate the sum of single-precision floating-point strided array elements, ignoring `NaN` values and using an improved Kahan–Babuška algorithm.</span>
 -   <span class="signature">[`snansumkbn2( N, x, stride )`][@stdlib/blas/ext/base/snansumkbn2]</span><span class="delimiter">: </span><span class="description">calculate the sum of single-precision floating-point strided array elements, ignoring `NaN` values and using a second-order iterative Kahan–Babuška algorithm.</span>
--   <span class="signature">[`snansumors( N, x, stride )`][@stdlib/blas/ext/base/snansumors]</span><span class="delimiter">: </span><span class="description">calculate the sum of single-precision floating-point strided array elements, ignoring `NaN` values and using ordinary recursive summation.</span>
+-   <span class="signature">[`snansumors( N, x, strideX )`][@stdlib/blas/ext/base/snansumors]</span><span class="delimiter">: </span><span class="description">calculate the sum of single-precision floating-point strided array elements, ignoring `NaN` values and using ordinary recursive summation.</span>
 -   <span class="signature">[`snansumpw( N, x, strideX )`][@stdlib/blas/ext/base/snansumpw]</span><span class="delimiter">: </span><span class="description">calculate the sum of single-precision floating-point strided array elements, ignoring `NaN` values and using pairwise summation.</span>
 -   <span class="signature">[`srev( N, x, stride )`][@stdlib/blas/ext/base/srev]</span><span class="delimiter">: </span><span class="description">reverse a single-precision floating-point strided array in-place.</span>
 -   <span class="signature">[`ssort2hp( N, order, x, strideX, y, strideY )`][@stdlib/blas/ext/base/ssort2hp]</span><span class="delimiter">: </span><span class="description">simultaneously sort two single-precision floating-point strided arrays based on the sort order of the first array using heapsort.</span>
diff --git a/lib/node_modules/@stdlib/stats/base/README.md b/lib/node_modules/@stdlib/stats/base/README.md
index d3453aa63213..287a5d04998e 100644
--- a/lib/node_modules/@stdlib/stats/base/README.md
+++ b/lib/node_modules/@stdlib/stats/base/README.md
@@ -85,7 +85,7 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`dmediansorted( N, x, stride )`][@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, stride )`][@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, stride )`][@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>
--   <span class="signature">[`dminabs( N, x, stride )`][@stdlib/stats/base/dminabs]</span><span class="delimiter">: </span><span class="description">calculate the minimum absolute value of a double-precision floating-point strided array.</span>
+-   <span class="signature">[`dminabs( N, x, strideX )`][@stdlib/stats/base/dminabs]</span><span class="delimiter">: </span><span class="description">calculate the minimum absolute value of a double-precision floating-point strided array.</span>
 -   <span class="signature">[`dminsorted( N, x, stride )`][@stdlib/stats/base/dminsorted]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a sorted double-precision floating-point strided array.</span>
 -   <span class="signature">[`dmskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/dmskmax]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a double-precision floating-point strided array according to a mask.</span>
 -   <span class="signature">[`dmskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/dmskmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a double-precision floating-point strided array according to a mask.</span>
@@ -98,7 +98,7 @@ The namespace contains the following statistical functions:
 -   <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">[`dnanmin( N, x, stride )`][@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, stride )`][@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">[`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>
 -   <span class="signature">[`dnanmskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/dnanmskmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a double-precision floating-point strided array according to a mask, ignoring `NaN` values.</span>
 -   <span class="signature">[`dnanmskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/dnanmskrange]</span><span class="delimiter">: </span><span class="description">calculate the range of a double-precision floating-point strided array according to a mask, ignoring `NaN` values.</span>
@@ -115,7 +115,7 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`dnanvariancetk( N, correction, x, stride )`][@stdlib/stats/base/dnanvariancetk]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass textbook algorithm.</span>
 -   <span class="signature">[`dnanvariancewd( N, correction, x, stride )`][@stdlib/stats/base/dnanvariancewd]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array ignoring `NaN` values and using Welford's algorithm.</span>
 -   <span class="signature">[`dnanvarianceyc( N, correction, x, stride )`][@stdlib/stats/base/dnanvarianceyc]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer.</span>
--   <span class="signature">[`drange( N, x, stride )`][@stdlib/stats/base/drange]</span><span class="delimiter">: </span><span class="description">calculate the range of a double-precision floating-point strided array.</span>
+-   <span class="signature">[`drange( N, x, strideX )`][@stdlib/stats/base/drange]</span><span class="delimiter">: </span><span class="description">calculate the range of a double-precision floating-point strided array.</span>
 -   <span class="signature">[`dsem( N, correction, x, stride )`][@stdlib/stats/base/dsem]</span><span class="delimiter">: </span><span class="description">calculate the standard error of the mean of a double-precision floating-point strided array.</span>
 -   <span class="signature">[`dsemch( N, correction, x, stride )`][@stdlib/stats/base/dsemch]</span><span class="delimiter">: </span><span class="description">calculate the standard error of the mean of a double-precision floating-point strided array using a one-pass trial mean algorithm.</span>
 -   <span class="signature">[`dsempn( N, correction, x, stride )`][@stdlib/stats/base/dsempn]</span><span class="delimiter">: </span><span class="description">calculate the standard error of the mean of a double-precision floating-point strided array using a two-pass algorithm.</span>