docs: update namespace table of contents

PR-URL: #5332
Reviewed-by: Athan Reines <[email protected]>

Author: stdlib-bot

lib/node_modules/@stdlib/math/base/ops/README.md

@@ -50,11 +50,9 @@ The namespace contains the following functions:
 -   <span class="signature">[`cnegf( z )`][@stdlib/math/base/ops/cnegf]</span><span class="delimiter">: </span><span class="description">negate a single-precision complex floating-point number.</span>
 -   <span class="signature">[`csub( z1, z2 )`][@stdlib/math/base/ops/csub]</span><span class="delimiter">: </span><span class="description">subtract two double-precision complex floating-point numbers.</span>
 -   <span class="signature">[`csubf( z1, z2 )`][@stdlib/math/base/ops/csubf]</span><span class="delimiter">: </span><span class="description">subtract two single-precision complex floating-point numbers.</span>
--   <span class="signature">[`div( x, y )`][@stdlib/number/float64/base/div]</span><span class="delimiter">: </span><span class="description">divide two double-precision floating-point numbers.</span>
 -   <span class="signature">[`divf( x, y )`][@stdlib/math/base/ops/divf]</span><span class="delimiter">: </span><span class="description">divide two single-precision floating-point numbers.</span>
 -   <span class="signature">[`imul( a, b )`][@stdlib/math/base/ops/imul]</span><span class="delimiter">: </span><span class="description">perform C-like multiplication of two signed 32-bit integers.</span>
 -   <span class="signature">[`imuldw( a, b )`][@stdlib/math/base/ops/imuldw]</span><span class="delimiter">: </span><span class="description">compute the double word product of two signed 32-bit integers.</span>
--   <span class="signature">[`mul( x, y )`][@stdlib/number/float64/base/mul]</span><span class="delimiter">: </span><span class="description">multiply two double-precision floating-point numbers.</span>
 -   <span class="signature">[`mulf( x, y )`][@stdlib/math/base/ops/mulf]</span><span class="delimiter">: </span><span class="description">multiply two single-precision floating-point numbers.</span>
 -   <span class="signature">[`sub( x, y )`][@stdlib/math/base/ops/sub]</span><span class="delimiter">: </span><span class="description">subtract two double-precision floating-point numbers.</span>
 -   <span class="signature">[`subf( x, y )`][@stdlib/math/base/ops/subf]</span><span class="delimiter">: </span><span class="description">subtract two single-precision floating-point numbers.</span>
@@ -141,16 +139,12 @@ console.log( ns.imuldw( 0x80000000|0, 0x40000000|0 ) );
 
 [@stdlib/math/base/ops/csubf]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/ops/csubf
 
-[@stdlib/number/float64/base/div]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/number/float64/base/div
-
 [@stdlib/math/base/ops/divf]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/ops/divf
 
 [@stdlib/math/base/ops/imul]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/ops/imul
 
 [@stdlib/math/base/ops/imuldw]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/ops/imuldw
 
-[@stdlib/number/float64/base/mul]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/number/float64/base/mul
-
 [@stdlib/math/base/ops/mulf]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/ops/mulf
 
 [@stdlib/math/base/ops/sub]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/ops/sub

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

@@ -68,18 +68,13 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`dmeanstdevpn( N, correction, x, strideX, out, strideOut )`][@stdlib/stats/base/dmeanstdevpn]</span><span class="delimiter">: </span><span class="description">calculate the mean and standard deviation of a double-precision floating-point strided array using a two-pass algorithm.</span>
 -   <span class="signature">[`dmeanvar( N, correction, x, strideX, out, strideOut )`][@stdlib/stats/base/dmeanvar]</span><span class="delimiter">: </span><span class="description">calculate the mean and variance of a double-precision floating-point strided array.</span>
 -   <span class="signature">[`dmeanvarpn( N, correction, x, strideX, out, strideOut )`][@stdlib/stats/base/dmeanvarpn]</span><span class="delimiter">: </span><span class="description">calculate the mean and variance of a double-precision floating-point strided array using a two-pass algorithm.</span>
--   <span class="signature">[`dmeanwd( N, x, strideX )`][@stdlib/stats/strided/dmeanwd]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using Welford's algorithm.</span>
--   <span class="signature">[`dmediansorted( N, x, strideX )`][@stdlib/stats/strided/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, strideX )`][@stdlib/stats/strided/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, strideX )`][@stdlib/stats/strided/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, strideX )`][@stdlib/stats/strided/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, strideX )`][@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>
 -   <span class="signature">[`dmskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/dmskrange]</span><span class="delimiter">: </span><span class="description">calculate the range of a double-precision floating-point strided array according to a mask.</span>
 -   <span class="signature">[`dnanmax( N, x, strideX )`][@stdlib/stats/base/dnanmax]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a double-precision floating-point strided array, ignoring `NaN` values.</span>
 -   <span class="signature">[`dnanmaxabs( N, x, strideX )`][@stdlib/stats/base/dnanmaxabs]</span><span class="delimiter">: </span><span class="description">calculate the maximum absolute value of a double-precision floating-point strided array, ignoring `NaN` values.</span>
--   <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">[`dnanmean( N, x, strideX )`][@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, strideX )`][@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, strideX )`][@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, 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>
@@ -99,7 +94,7 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`dnanvariance( N, correction, x, stride )`][@stdlib/stats/base/dnanvariance]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array ignoring `NaN` values.</span>
 -   <span class="signature">[`dnanvariancech( N, correction, x, stride )`][@stdlib/stats/base/dnanvariancech]</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 trial mean algorithm.</span>
 -   <span class="signature">[`dnanvariancepn( N, correction, x, stride )`][@stdlib/stats/base/dnanvariancepn]</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 two-pass algorithm.</span>
--   <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">[`dnanvariancetk( N, correction, x, strideX )`][@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, 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>
@@ -333,16 +328,6 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/stats/base/dmeanvarpn]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dmeanvarpn
 
-[@stdlib/stats/strided/dmeanwd]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmeanwd
-
-[@stdlib/stats/strided/dmediansorted]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmediansorted
-
-[@stdlib/stats/strided/dmidrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmidrange
-
-[@stdlib/stats/strided/dmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmin
-
-[@stdlib/stats/strided/dminabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dminabs
-
 [@stdlib/stats/base/dminsorted]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dminsorted
 
 [@stdlib/stats/base/dmskmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dmskmax