docs: update namespace table of contents

PR-URL: #9967

Reviewed-by: Philipp Burckhardt <pburckhardt@outlook.com>
Signed-off-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>

Author: stdlib-bot

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

@@ -90,6 +90,7 @@ The namespace exposes the following APIs:
 -   <span class="signature">[`dnanmskrange( arrays )`][@stdlib/stats/base/ndarray/dnanmskrange]</span><span class="delimiter">: </span><span class="description">calculate the range of a one-dimensional double-precision floating-point ndarray according to a mask, ignoring `NaN` values.</span>
 -   <span class="signature">[`dnanrange( arrays )`][@stdlib/stats/base/ndarray/dnanrange]</span><span class="delimiter">: </span><span class="description">compute the range of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.</span>
 -   <span class="signature">[`drange( arrays )`][@stdlib/stats/base/ndarray/drange]</span><span class="delimiter">: </span><span class="description">compute the range of a one-dimensional double-precision floating-point ndarray.</span>
+-   <span class="signature">[`drangeabs( arrays )`][@stdlib/stats/base/ndarray/drangeabs]</span><span class="delimiter">: </span><span class="description">compute the range of absolute values of a one-dimensional double-precision floating-point ndarray.</span>
 -   <span class="signature">[`dstdev( arrays )`][@stdlib/stats/base/ndarray/dstdev]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a one-dimensional double-precision floating-point ndarray.</span>
 -   <span class="signature">[`dstdevch( arrays )`][@stdlib/stats/base/ndarray/dstdevch]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a one-dimensional double-precision floating-point ndarray using a one-pass trial mean algorithm.</span>
 -   <span class="signature">[`dstdevpn( arrays )`][@stdlib/stats/base/ndarray/dstdevpn]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a one-dimensional double-precision floating-point ndarray using a two-pass algorithm.</span>
@@ -137,6 +138,7 @@ The namespace exposes the following APIs:
 -   <span class="signature">[`nanrange( arrays )`][@stdlib/stats/base/ndarray/nanrange]</span><span class="delimiter">: </span><span class="description">compute the range of a one-dimensional ndarray, ignoring `NaN` values.</span>
 -   <span class="signature">[`rangeBy( arrays, clbk[, thisArg ] )`][@stdlib/stats/base/ndarray/range-by]</span><span class="delimiter">: </span><span class="description">calculate the range of a one-dimensional ndarray via a callback function.</span>
 -   <span class="signature">[`range( arrays )`][@stdlib/stats/base/ndarray/range]</span><span class="delimiter">: </span><span class="description">compute the range of a one-dimensional ndarray.</span>
+-   <span class="signature">[`rangeabs( arrays )`][@stdlib/stats/base/ndarray/rangeabs]</span><span class="delimiter">: </span><span class="description">compute the range of absolute values of a one-dimensional ndarray.</span>
 -   <span class="signature">[`scovarmtk( arrays )`][@stdlib/stats/base/ndarray/scovarmtk]</span><span class="delimiter">: </span><span class="description">calculate the covariance of two one-dimensional single-precision floating-point ndarrays provided known means and using a one-pass textbook algorithm.</span>
 -   <span class="signature">[`scumax( arrays )`][@stdlib/stats/base/ndarray/scumax]</span><span class="delimiter">: </span><span class="description">compute the cumulative maximum value of a one-dimensional single-precision floating-point ndarray.</span>
 -   <span class="signature">[`scumaxabs( arrays )`][@stdlib/stats/base/ndarray/scumaxabs]</span><span class="delimiter">: </span><span class="description">compute the cumulative maximum absolute value of a one-dimensional single-precision floating-point ndarray.</span>
@@ -181,6 +183,7 @@ The namespace exposes the following APIs:
 -   <span class="signature">[`snanmskrange( arrays )`][@stdlib/stats/base/ndarray/snanmskrange]</span><span class="delimiter">: </span><span class="description">calculate the range of a one-dimensional single-precision floating-point ndarray according to a mask, ignoring `NaN` values.</span>
 -   <span class="signature">[`snanrange( arrays )`][@stdlib/stats/base/ndarray/snanrange]</span><span class="delimiter">: </span><span class="description">compute the range of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values.</span>
 -   <span class="signature">[`srange( arrays )`][@stdlib/stats/base/ndarray/srange]</span><span class="delimiter">: </span><span class="description">compute the range of a one-dimensional single-precision floating-point ndarray.</span>
+-   <span class="signature">[`srangeabs( arrays )`][@stdlib/stats/base/ndarray/srangeabs]</span><span class="delimiter">: </span><span class="description">compute the range of absolute values of a one-dimensional single-precision floating-point ndarray.</span>
 -   <span class="signature">[`sstdev( arrays )`][@stdlib/stats/base/ndarray/sstdev]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a one-dimensional single-precision floating-point ndarray.</span>
 -   <span class="signature">[`sstdevch( arrays )`][@stdlib/stats/base/ndarray/sstdevch]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a one-dimensional single-precision floating-point ndarray using a one-pass trial mean algorithm.</span>
 -   <span class="signature">[`sstdevpn( arrays )`][@stdlib/stats/base/ndarray/sstdevpn]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a one-dimensional single-precision floating-point ndarray using a two-pass algorithm.</span>
@@ -330,6 +333,8 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/stats/base/ndarray/drange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/drange
 
+[@stdlib/stats/base/ndarray/drangeabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/drangeabs
+
 [@stdlib/stats/base/ndarray/dstdev]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/dstdev
 
 [@stdlib/stats/base/ndarray/dstdevch]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/dstdevch
@@ -424,6 +429,8 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/stats/base/ndarray/range]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/range
 
+[@stdlib/stats/base/ndarray/rangeabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/rangeabs
+
 [@stdlib/stats/base/ndarray/scovarmtk]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/scovarmtk
 
 [@stdlib/stats/base/ndarray/scumax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/scumax
@@ -512,6 +519,8 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/stats/base/ndarray/srange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/srange
 
+[@stdlib/stats/base/ndarray/srangeabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/srangeabs
+
 [@stdlib/stats/base/ndarray/sstdev]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/sstdev
 
 [@stdlib/stats/base/ndarray/sstdevch]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/sstdevch