diff --git a/lib/node_modules/@stdlib/blas/ext/base/README.md b/lib/node_modules/@stdlib/blas/ext/base/README.md
index 76a01be4de7a..1ee952c9ebd3 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/README.md
+++ b/lib/node_modules/@stdlib/blas/ext/base/README.md
@@ -121,8 +121,8 @@ var ns = extblas;
 -   <span class="signature">[`gsumkbn2( N, x, strideX )`][@stdlib/blas/ext/base/gsumkbn2]</span><span class="delimiter">: </span><span class="description">calculate the sum of strided array elements using a second-order iterative Kahan–Babuška algorithm.</span>
 -   <span class="signature">[`gsumors( N, x, strideX )`][@stdlib/blas/ext/base/gsumors]</span><span class="delimiter">: </span><span class="description">calculate the sum of strided array elements using ordinary recursive summation.</span>
 -   <span class="signature">[`gsumpw( N, x, strideX )`][@stdlib/blas/ext/base/gsumpw]</span><span class="delimiter">: </span><span class="description">calculate the sum of strided array elements using pairwise summation.</span>
--   <span class="signature">[`sapx( N, alpha, x, stride )`][@stdlib/blas/ext/base/sapx]</span><span class="delimiter">: </span><span class="description">add a constant to each element in a single-precision floating-point strided array.</span>
--   <span class="signature">[`sapxsum( N, alpha, x, stride )`][@stdlib/blas/ext/base/sapxsum]</span><span class="delimiter">: </span><span class="description">add a constant to each single-precision floating-point strided array element and compute the sum.</span>
+-   <span class="signature">[`sapx( N, alpha, x, strideX )`][@stdlib/blas/ext/base/sapx]</span><span class="delimiter">: </span><span class="description">add a scalar constant to each element in a single-precision floating-point strided array.</span>
+-   <span class="signature">[`sapxsum( N, alpha, x, strideX )`][@stdlib/blas/ext/base/sapxsum]</span><span class="delimiter">: </span><span class="description">add a scalar constant to each single-precision floating-point strided array element and compute the sum.</span>
 -   <span class="signature">[`sapxsumkbn( N, alpha, x, strideX )`][@stdlib/blas/ext/base/sapxsumkbn]</span><span class="delimiter">: </span><span class="description">add a scalar constant to each single-precision floating-point strided array element and compute the sum using an improved Kahan–Babuška algorithm.</span>
 -   <span class="signature">[`sapxsumkbn2( N, alpha, x, strideX )`][@stdlib/blas/ext/base/sapxsumkbn2]</span><span class="delimiter">: </span><span class="description">add a scalar constant to each single-precision floating-point strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm.</span>
 -   <span class="signature">[`sapxsumors( N, alpha, x, strideX )`][@stdlib/blas/ext/base/sapxsumors]</span><span class="delimiter">: </span><span class="description">add a scalar constant to each single-precision floating-point strided array element and compute the sum using ordinary recursive summation.</span>
diff --git a/lib/node_modules/@stdlib/stats/base/README.md b/lib/node_modules/@stdlib/stats/base/README.md
index d01dd353a3df..8bb7e77f9887 100644
--- a/lib/node_modules/@stdlib/stats/base/README.md
+++ b/lib/node_modules/@stdlib/stats/base/README.md
@@ -94,7 +94,7 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`dnanmean( N, x, stride )`][@stdlib/stats/base/dnanmean]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values.</span>
 -   <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">[`dnanmeanpw( N, x, strideX )`][@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, 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>
@@ -124,7 +124,7 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`dsmean( N, x, stride )`][@stdlib/stats/base/dsmean]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using extended accumulation and returning an extended precision result.</span>
 -   <span class="signature">[`dsmeanors( N, x, strideX )`][@stdlib/stats/base/dsmeanors]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and returning an extended precision result.</span>
 -   <span class="signature">[`dsmeanpn( N, x, strideX )`][@stdlib/stats/base/dsmeanpn]</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 with extended accumulation and returning an extended precision result.</span>
--   <span class="signature">[`dsmeanpw( N, x, stride )`][@stdlib/stats/base/dsmeanpw]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using pairwise summation with extended accumulation and returning an extended precision result.</span>
+-   <span class="signature">[`dsmeanpw( N, x, strideX )`][@stdlib/stats/base/dsmeanpw]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using pairwise summation with extended accumulation and returning an extended precision result.</span>
 -   <span class="signature">[`dsmeanwd( N, x, strideX )`][@stdlib/stats/base/dsmeanwd]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm with extended accumulation and returning an extended precision result.</span>
 -   <span class="signature">[`dsnanmean( N, x, stride )`][@stdlib/stats/base/dsnanmean]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values, using extended accumulation, and returning an extended precision result.</span>
 -   <span class="signature">[`dsnanmeanors( N, x, stride )`][@stdlib/stats/base/dsnanmeanors]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values, using ordinary recursive summation with extended accumulation, and returning an extended precision result.</span>
@@ -210,7 +210,7 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`smean( N, x, stride )`][@stdlib/stats/base/smean]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array.</span>
 -   <span class="signature">[`smeankbn( N, x, stride )`][@stdlib/stats/base/smeankbn]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using an improved Kahan–Babuška algorithm.</span>
 -   <span class="signature">[`smeankbn2( N, x, stride )`][@stdlib/stats/base/smeankbn2]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm.</span>
--   <span class="signature">[`smeanli( N, x, stride )`][@stdlib/stats/base/smeanli]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using a one-pass trial mean algorithm.</span>
+-   <span class="signature">[`smeanli( N, x, strideX )`][@stdlib/stats/base/smeanli]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using a one-pass trial mean algorithm.</span>
 -   <span class="signature">[`smeanlipw( N, x, stride )`][@stdlib/stats/base/smeanlipw]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using a one-pass trial mean algorithm with pairwise summation.</span>
 -   <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>