docs: update namespace table of contents

PR-URL: #11712
Reviewed-by: Athan Reines <kgryte@gmail.com>
Reviewed-by: Philipp Burckhardt <pburckhardt@outlook.com>

Author: stdlib-bot

lib/node_modules/@stdlib/blas/ext/base/README.md

@@ -62,6 +62,7 @@ var o = ns;
 -   <span class="signature">[`dcusumkbn2( N, sum, x, strideX, y, strideY )`][@stdlib/blas/ext/base/dcusumkbn2]</span><span class="delimiter">: </span><span class="description">calculate the cumulative sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm.</span>
 -   <span class="signature">[`dcusumors( N, sum, x, strideX, y, strideY )`][@stdlib/blas/ext/base/dcusumors]</span><span class="delimiter">: </span><span class="description">calculate the cumulative sum of double-precision floating-point strided array elements using ordinary recursive summation.</span>
 -   <span class="signature">[`dcusumpw( N, sum, x, strideX, y, strideY )`][@stdlib/blas/ext/base/dcusumpw]</span><span class="delimiter">: </span><span class="description">calculate the cumulative sum of double-precision floating-point strided array elements using pairwise summation.</span>
+-   <span class="signature">[`ddiff( N, k, x, strideX, N1, prepend, strideP, N2, append, strideA, out, strideOut, workspace, strideW )`][@stdlib/blas/ext/base/ddiff]</span><span class="delimiter">: </span><span class="description">calculate the k-th discrete forward difference of a double-precision floating-point strided array.</span>
 -   <span class="signature">[`dfill( N, alpha, x, strideX )`][@stdlib/blas/ext/base/dfill]</span><span class="delimiter">: </span><span class="description">fill a double-precision floating-point strided array with a specified scalar constant.</span>
 -   <span class="signature">[`dindexOfRow( order, M, N, A, LDA, x, strideX, workspace, strideW )`][@stdlib/blas/ext/base/dindex-of-row]</span><span class="delimiter">: </span><span class="description">return the index of the first row in a double-precision floating-point input matrix which has the same elements as a provided search vector.</span>
 -   <span class="signature">[`dindexOf( N, searchElement, x, strideX )`][@stdlib/blas/ext/base/dindex-of]</span><span class="delimiter">: </span><span class="description">return the first index of a specified search element in a double-precision floating-point strided array.</span>
@@ -307,6 +308,8 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/blas/ext/base/dcusumpw]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dcusumpw
 
+[@stdlib/blas/ext/base/ddiff]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ddiff
+
 [@stdlib/blas/ext/base/dfill]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dfill
 
 [@stdlib/blas/ext/base/dindex-of-row]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dindex-of-row

lib/node_modules/@stdlib/stats/README.md

@@ -140,6 +140,7 @@ Other statistical functions included are:
 -   <span class="signature">[`nanmeanpn( x[, options] )`][@stdlib/stats/nanmeanpn]</span><span class="delimiter">: </span><span class="description">compute the arithmetic mean along one or more ndarray dimensions, ignoring `NaN` values and using a two-pass error correction algorithm.</span>
 -   <span class="signature">[`nanmeanwd( x[, options] )`][@stdlib/stats/nanmeanwd]</span><span class="delimiter">: </span><span class="description">compute the arithmetic mean along one or more ndarray dimensions, ignoring `NaN` values and using Welford's algorithm.</span>
 -   <span class="signature">[`nanmidrangeBy( x[, options], clbk[, thisArg] )`][@stdlib/stats/nanmidrange-by]</span><span class="delimiter">: </span><span class="description">compute the **mid-range** along one or more ndarray dimensions according to a callback function, ignoring `NaN` values.</span>
+-   <span class="signature">[`nanmidrange( x[, options] )`][@stdlib/stats/nanmidrange]</span><span class="delimiter">: </span><span class="description">compute the **mid-range** along one or more ndarray dimensions, ignoring `NaN` values.</span>
 -   <span class="signature">[`nanminBy( x[, options], clbk[, thisArg] )`][@stdlib/stats/nanmin-by]</span><span class="delimiter">: </span><span class="description">compute the minimum value along one or more ndarray dimensions according to a callback function, ignoring `NaN` values.</span>
 -   <span class="signature">[`nanmin( x[, options] )`][@stdlib/stats/nanmin]</span><span class="delimiter">: </span><span class="description">compute the minimum value along one or more ndarray dimensions, ignoring `NaN` values.</span>
 -   <span class="signature">[`nanminabs( x[, options] )`][@stdlib/stats/nanminabs]</span><span class="delimiter">: </span><span class="description">compute the minimum absolute value along one or more ndarray dimensions, ignoring `NaN` values.</span>
@@ -252,6 +253,8 @@ console.log( objectKeys( statistics ) );
 
 [@stdlib/stats/nanmidrange-by]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/nanmidrange-by
 
+[@stdlib/stats/nanmidrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/nanmidrange
+
 [@stdlib/stats/nanmin-by]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/nanmin-by
 
 [@stdlib/stats/nanmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/nanmin