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docs: update namespace table of contents #5965

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4 changes: 2 additions & 2 deletions lib/node_modules/@stdlib/stats/base/README.md
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Expand Up @@ -83,8 +83,8 @@ The namespace contains the following statistical functions:
- <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">[`dnanstdevtk( N, correction, x, stride )`][@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, stride )`][@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">[`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, stride )`][@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">[`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>
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