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docs: update namespace table of contents #4489

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4 changes: 2 additions & 2 deletions lib/node_modules/@stdlib/blas/ext/base/README.md
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Expand Up @@ -86,12 +86,12 @@ var ns = extblas;
- <span class="signature">[`dssumpw( N, x, strideX )`][@stdlib/blas/ext/base/dssumpw]</span><span class="delimiter">: </span><span class="description">calculate the sum of single-precision floating-point strided array elements using pairwise summation with extended accumulation and returning an extended precision result.</span>
- <span class="signature">[`dsum( N, x, strideX )`][@stdlib/blas/ext/base/dsum]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements.</span>
- <span class="signature">[`dsumkbn( N, x, strideX )`][@stdlib/blas/ext/base/dsumkbn]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements using an improved Kahan–Babuška algorithm.</span>
- <span class="signature">[`dsumkbn2( N, x, stride )`][@stdlib/blas/ext/base/dsumkbn2]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm.</span>
- <span class="signature">[`dsumkbn2( N, x, strideX )`][@stdlib/blas/ext/base/dsumkbn2]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm.</span>
- <span class="signature">[`dsumors( N, x, stride )`][@stdlib/blas/ext/base/dsumors]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements using ordinary recursive summation.</span>
- <span class="signature">[`dsumpw( N, x, stride )`][@stdlib/blas/ext/base/dsumpw]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements using pairwise summation.</span>
- <span class="signature">[`gapx( N, alpha, x, stride )`][@stdlib/blas/ext/base/gapx]</span><span class="delimiter">: </span><span class="description">add a constant to each element in a strided array.</span>
- <span class="signature">[`gapxsum( N, alpha, x, stride )`][@stdlib/blas/ext/base/gapxsum]</span><span class="delimiter">: </span><span class="description">add a constant to each strided array element and compute the sum.</span>
- <span class="signature">[`gapxsumkbn( N, alpha, x, stride )`][@stdlib/blas/ext/base/gapxsumkbn]</span><span class="delimiter">: </span><span class="description">add a constant to each strided array element and compute the sum using an improved Kahan–Babuška algorithm.</span>
- <span class="signature">[`gapxsumkbn( N, alpha, x, strideX )`][@stdlib/blas/ext/base/gapxsumkbn]</span><span class="delimiter">: </span><span class="description">add a scalar constant to each strided array element and compute the sum using an improved Kahan–Babuška algorithm.</span>
- <span class="signature">[`gapxsumkbn2( N, alpha, x, stride )`][@stdlib/blas/ext/base/gapxsumkbn2]</span><span class="delimiter">: </span><span class="description">add a constant to each strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm.</span>
- <span class="signature">[`gapxsumors( N, alpha, x, stride )`][@stdlib/blas/ext/base/gapxsumors]</span><span class="delimiter">: </span><span class="description">add a constant to each strided array element and compute the sum using ordinary recursive summation.</span>
- <span class="signature">[`gapxsumpw( N, alpha, x, stride )`][@stdlib/blas/ext/base/gapxsumpw]</span><span class="delimiter">: </span><span class="description">add a constant to each strided array element and compute the sum using pairwise summation.</span>
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10 changes: 5 additions & 5 deletions lib/node_modules/@stdlib/stats/base/README.md
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Expand Up @@ -67,8 +67,8 @@ The namespace contains the following statistical functions:
- <span class="signature">[`dcuminabs( N, x, strideX, y, strideY )`][@stdlib/stats/base/dcuminabs]</span><span class="delimiter">: </span><span class="description">calculate the cumulative minimum absolute value of double-precision floating-point strided array elements.</span>
- <span class="signature">[`dmax( N, x, strideX )`][@stdlib/stats/base/dmax]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a double-precision floating-point strided array.</span>
- <span class="signature">[`dmaxabs( N, x, strideX )`][@stdlib/stats/base/dmaxabs]</span><span class="delimiter">: </span><span class="description">calculate the maximum absolute value of a double-precision floating-point strided array.</span>
- <span class="signature">[`dmaxabssorted( N, x, stride )`][@stdlib/stats/base/dmaxabssorted]</span><span class="delimiter">: </span><span class="description">calculate the maximum absolute value of a sorted double-precision floating-point strided array.</span>
- <span class="signature">[`dmaxsorted( N, x, stride )`][@stdlib/stats/base/dmaxsorted]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a sorted double-precision floating-point strided array.</span>
- <span class="signature">[`dmaxabssorted( N, x, strideX )`][@stdlib/stats/base/dmaxabssorted]</span><span class="delimiter">: </span><span class="description">calculate the maximum absolute value of a sorted double-precision floating-point strided array.</span>
- <span class="signature">[`dmaxsorted( N, x, strideX )`][@stdlib/stats/base/dmaxsorted]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a sorted double-precision floating-point strided array.</span>
- <span class="signature">[`dmean( N, x, stride )`][@stdlib/stats/base/dmean]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array.</span>
- <span class="signature">[`dmeankbn( N, x, stride )`][@stdlib/stats/base/dmeankbn]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm.</span>
- <span class="signature">[`dmeankbn2( N, x, stride )`][@stdlib/stats/base/dmeankbn2]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm.</span>
Expand All @@ -82,11 +82,11 @@ The namespace contains the following statistical functions:
- <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, stride )`][@stdlib/stats/base/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, stride )`][@stdlib/stats/base/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">[`dmediansorted( N, x, strideX )`][@stdlib/stats/base/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/base/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/base/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/base/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, stride )`][@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">[`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>
Expand Down Expand Up @@ -206,7 +206,7 @@ The namespace contains the following statistical functions:
- <span class="signature">[`sdsnanmeanors( N, x, stride )`][@stdlib/stats/base/sdsnanmeanors]</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 with extended accumulation.</span>
- <span class="signature">[`smax( N, x, strideX )`][@stdlib/stats/base/smax]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a single-precision floating-point strided array.</span>
- <span class="signature">[`smaxabs( N, x, strideX )`][@stdlib/stats/base/smaxabs]</span><span class="delimiter">: </span><span class="description">calculate the maximum absolute value of a single-precision floating-point strided array.</span>
- <span class="signature">[`smaxabssorted( N, x, stride )`][@stdlib/stats/base/smaxabssorted]</span><span class="delimiter">: </span><span class="description">calculate the maximum absolute value of a sorted single-precision floating-point strided array.</span>
- <span class="signature">[`smaxabssorted( N, x, strideX )`][@stdlib/stats/base/smaxabssorted]</span><span class="delimiter">: </span><span class="description">calculate the maximum absolute value of a sorted single-precision floating-point strided array.</span>
- <span class="signature">[`smaxsorted( N, x, stride )`][@stdlib/stats/base/smaxsorted]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a sorted single-precision floating-point strided array.</span>
- <span class="signature">[`smean( N, x, stride )`][@stdlib/stats/base/smean]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array.</span>
- <span class="signature">[`smeankbn( N, x, stride )`][@stdlib/stats/base/smeankbn]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using an improved Kahan–Babuška algorithm.</span>
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