diff --git a/lib/node_modules/@stdlib/ndarray/README.md b/lib/node_modules/@stdlib/ndarray/README.md
index dfe3c7bf3606..475a44c64e62 100644
--- a/lib/node_modules/@stdlib/ndarray/README.md
+++ b/lib/node_modules/@stdlib/ndarray/README.md
@@ -83,7 +83,7 @@ In addition, the namespace contains the following multidimensional array utility
 -   <span class="signature">[`emptyLike( x[, options] )`][@stdlib/ndarray/empty-like]</span><span class="delimiter">: </span><span class="description">create an uninitialized ndarray having the same shape and data type as a provided ndarray.</span>
 -   <span class="signature">[`empty( shape[, options] )`][@stdlib/ndarray/empty]</span><span class="delimiter">: </span><span class="description">create an uninitialized ndarray having a specified shape and data type.</span>
 -   <span class="signature">[`FancyArray( dtype, buffer, shape, strides, offset, order[, options] )`][@stdlib/ndarray/fancy]</span><span class="delimiter">: </span><span class="description">fancy multidimensional array constructor.</span>
--   <span class="signature">[`fillBy( x, fcn[, thisArg] )`][@stdlib/ndarray/fill-by]</span><span class="delimiter">: </span><span class="description">fill an input `ndarray` according to a callback function.</span>
+-   <span class="signature">[`fillBy( x, fcn[, thisArg] )`][@stdlib/ndarray/fill-by]</span><span class="delimiter">: </span><span class="description">fill an input ndarray according to a callback function.</span>
 -   <span class="signature">[`fill( x, value )`][@stdlib/ndarray/fill]</span><span class="delimiter">: </span><span class="description">fill an input `ndarray` with a specified value.</span>
 -   <span class="signature">[`filterMap( x[, options], fcn[, thisArg] )`][@stdlib/ndarray/filter-map]</span><span class="delimiter">: </span><span class="description">filter and map elements in an input ndarray to elements in a new output ndarray according to a callback function.</span>
 -   <span class="signature">[`filter( x[, options], predicate[, thisArg] )`][@stdlib/ndarray/filter]</span><span class="delimiter">: </span><span class="description">return a shallow copy of an ndarray containing only those elements which pass a test implemented by a predicate function.</span>
diff --git a/lib/node_modules/@stdlib/stats/base/README.md b/lib/node_modules/@stdlib/stats/base/README.md
index 39799da50934..f27a7dd8ef1a 100644
--- a/lib/node_modules/@stdlib/stats/base/README.md
+++ b/lib/node_modules/@stdlib/stats/base/README.md
@@ -70,7 +70,7 @@ The namespace contains the following statistical functions:
 -   <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>
--   <span class="signature">[`dnanstdev( N, correction, x, stride )`][@stdlib/stats/base/dnanstdev]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array ignoring `NaN` values.</span>
+-   <span class="signature">[`dnanstdev( N, correction, x, strideX )`][@stdlib/stats/base/dnanstdev]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array ignoring `NaN` values.</span>
 -   <span class="signature">[`dsem( N, correction, x, strideX )`][@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">[`dsempn( N, correction, x, strideX )`][@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>
 -   <span class="signature">[`dstdev( N, correction, x, strideX )`][@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>
@@ -103,7 +103,7 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`nanmeanpn( N, x, stride )`][@stdlib/stats/base/nanmeanpn]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a strided array, ignoring `NaN` values and using a two-pass error correction algorithm.</span>
 -   <span class="signature">[`nanmeanwd( N, x, stride )`][@stdlib/stats/base/nanmeanwd]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a strided array, ignoring `NaN` values and using Welford's algorithm.</span>
 -   <span class="signature">[`nanminBy( N, x, stride, clbk[, thisArg] )`][@stdlib/stats/base/nanmin-by]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a strided array via a callback function, ignoring `NaN` values.</span>
--   <span class="signature">[`nanmin( N, x, stride )`][@stdlib/stats/base/nanmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a strided array, ignoring `NaN` values.</span>
+-   <span class="signature">[`nanmin( N, x, strideX )`][@stdlib/stats/base/nanmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a strided array, ignoring `NaN` values.</span>
 -   <span class="signature">[`nanminabs( N, x, stride )`][@stdlib/stats/base/nanminabs]</span><span class="delimiter">: </span><span class="description">calculate the minimum absolute value of a strided array, ignoring `NaN` values.</span>
 -   <span class="signature">[`nanmskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/nanmskmax]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a strided array according to a mask, ignoring `NaN` values.</span>
 -   <span class="signature">[`nanmskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/nanmskmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a strided array according to a mask, ignoring `NaN` values.</span>