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docs: update namespace table of contents #6060

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3 changes: 0 additions & 3 deletions lib/node_modules/@stdlib/math/base/ops/README.md
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Expand Up @@ -45,7 +45,6 @@ The namespace contains the following functions:

<div class="namespace-toc">

- <span class="signature">[`cnegf( z )`][@stdlib/complex/float32/base/neg]</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>

Expand Down Expand Up @@ -89,8 +88,6 @@ console.log( ns );

<!-- <toc-links> -->

[@stdlib/complex/float32/base/neg]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/complex/float32/base/neg

[@stdlib/math/base/ops/csub]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/ops/csub

[@stdlib/math/base/ops/csubf]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/ops/csubf
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12 changes: 6 additions & 6 deletions lib/node_modules/@stdlib/stats/base/README.md
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Expand Up @@ -81,12 +81,12 @@ The namespace contains the following statistical functions:
- <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">[`dnanrange( N, x, strideX )`][@stdlib/stats/base/dnanrange]</span><span class="delimiter">: </span><span class="description">calculate the range of a double-precision floating-point strided array, 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">[`dnanstdevch( N, correction, x, stride )`][@stdlib/stats/base/dnanstdevch]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass trial mean algorithm.</span>
- <span class="signature">[`dnanstdevpn( N, correction, x, stride )`][@stdlib/stats/base/dnanstdevpn]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm.</span>
- <span class="signature">[`dnanstdevch( N, correction, x, strideX )`][@stdlib/stats/base/dnanstdevch]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass trial mean algorithm.</span>
- <span class="signature">[`dnanstdevpn( N, correction, x, strideX )`][@stdlib/stats/base/dnanstdevpn]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array, ignoring `NaN` values and using a two-pass algorithm.</span>
- <span class="signature">[`dnanstdevtk( N, correction, x, strideX )`][@stdlib/stats/base/dnanstdevtk]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass textbook algorithm.</span>
- <span class="signature">[`dnanstdevwd( N, correction, x, strideX )`][@stdlib/stats/base/dnanstdevwd]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array ignoring `NaN` values and using Welford's algorithm.</span>
- <span class="signature">[`dnanstdevyc( N, correction, x, strideX )`][@stdlib/stats/base/dnanstdevyc]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation 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">[`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">[`dnanvariance( N, correction, x, strideX )`][@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, strideX )`][@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, strideX )`][@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, 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>
Expand Down Expand Up @@ -115,7 +115,7 @@ The namespace contains the following statistical functions:
- <span class="signature">[`dstdevwd( N, correction, x, strideX )`][@stdlib/stats/base/dstdevwd]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array using Welford's algorithm.</span>
- <span class="signature">[`dstdevyc( N, correction, x, strideX )`][@stdlib/stats/base/dstdevyc]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer.</span>
- <span class="signature">[`dsvariance( N, correction, x, stride )`][@stdlib/stats/base/dsvariance]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array using extended accumulation and returning an extended precision result.</span>
- <span class="signature">[`dsvariancepn( N, correction, x, stride )`][@stdlib/stats/base/dsvariancepn]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array using a two-pass algorithm with extended accumulation and returning an extended precision result.</span>
- <span class="signature">[`dsvariancepn( N, correction, x, strideX )`][@stdlib/stats/base/dsvariancepn]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array using a two-pass algorithm with extended accumulation and returning an extended precision result.</span>
- <span class="signature">[`dvariance( N, correction, x, strideX )`][@stdlib/stats/base/dvariance]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array.</span>
- <span class="signature">[`dvariancech( N, correction, x, strideX )`][@stdlib/stats/base/dvariancech]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array using a one-pass trial mean algorithm.</span>
- <span class="signature">[`dvariancepn( N, correction, x, strideX )`][@stdlib/stats/base/dvariancepn]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array using a two-pass algorithm.</span>
Expand Down Expand Up @@ -206,8 +206,8 @@ The namespace contains the following statistical functions:
- <span class="signature">[`snanmaxabs( N, x, strideX )`][@stdlib/stats/base/snanmaxabs]</span><span class="delimiter">: </span><span class="description">calculate the maximum absolute value of a single-precision floating-point strided array, ignoring `NaN` values.</span>
- <span class="signature">[`snanmean( N, x, stride )`][@stdlib/stats/base/snanmean]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values.</span>
- <span class="signature">[`snanmeanors( N, x, strideX )`][@stdlib/stats/base/snanmeanors]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using ordinary recursive summation.</span>
- <span class="signature">[`snanmeanpn( N, x, stride )`][@stdlib/stats/base/snanmeanpn]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using a two-pass error correction algorithm.</span>
- <span class="signature">[`snanmeanwd( N, x, stride )`][@stdlib/stats/base/snanmeanwd]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using Welford's algorithm.</span>
- <span class="signature">[`snanmeanpn( N, x, strideX )`][@stdlib/stats/base/snanmeanpn]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using a two-pass error correction algorithm.</span>
- <span class="signature">[`snanmeanwd( N, x, strideX )`][@stdlib/stats/base/snanmeanwd]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using Welford's algorithm.</span>
- <span class="signature">[`snanmin( N, x, strideX )`][@stdlib/stats/base/snanmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a single-precision floating-point strided array, ignoring `NaN` values.</span>
- <span class="signature">[`snanminabs( N, x, strideX )`][@stdlib/stats/base/snanminabs]</span><span class="delimiter">: </span><span class="description">calculate the minimum absolute value of a single-precision floating-point strided array, ignoring `NaN` values.</span>
- <span class="signature">[`snanmskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/snanmskmax]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a single-precision floating-point strided array according to a mask, ignoring `NaN` values.</span>
Expand Down