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Copy file name to clipboardExpand all lines: lib/node_modules/@stdlib/blas/ext/base/README.md
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@@ -114,8 +114,8 @@ var ns = extblas;
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- <spanclass="signature">[`gsort2ins( N, order, x, strideX, y, strideY )`][@stdlib/blas/ext/base/gsort2ins]</span><spanclass="delimiter">: </span><spanclass="description">simultaneously sort two strided arrays based on the sort order of the first array using insertion sort.</span>
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- <spanclass="signature">[`gsort2sh( N, order, x, strideX, y, strideY )`][@stdlib/blas/ext/base/gsort2sh]</span><spanclass="delimiter">: </span><spanclass="description">simultaneously sort two strided arrays based on the sort order of the first array using Shellsort.</span>
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- <spanclass="signature">[`gsorthp( N, order, x, strideX )`][@stdlib/blas/ext/base/gsorthp]</span><spanclass="delimiter">: </span><spanclass="description">sort a strided array using heapsort.</span>
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- <spanclass="signature">[`gsortins( N, order, x, stride )`][@stdlib/blas/ext/base/gsortins]</span><spanclass="delimiter">: </span><spanclass="description">sort a strided array using insertion sort.</span>
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- <spanclass="signature">[`gsortsh( N, order, x, stride )`][@stdlib/blas/ext/base/gsortsh]</span><spanclass="delimiter">: </span><spanclass="description">sort a strided array using Shellsort.</span>
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- <spanclass="signature">[`gsortins( N, order, x, strideX )`][@stdlib/blas/ext/base/gsortins]</span><spanclass="delimiter">: </span><spanclass="description">sort a strided array using insertion sort.</span>
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- <spanclass="signature">[`gsortsh( N, order, x, strideX )`][@stdlib/blas/ext/base/gsortsh]</span><spanclass="delimiter">: </span><spanclass="description">sort a strided array using Shellsort.</span>
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- <spanclass="signature">[`gsum( N, x, strideX )`][@stdlib/blas/ext/base/gsum]</span><spanclass="delimiter">: </span><spanclass="description">calculate the sum of strided array elements.</span>
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- <spanclass="signature">[`gsumkbn( N, x, strideX )`][@stdlib/blas/ext/base/gsumkbn]</span><spanclass="delimiter">: </span><spanclass="description">calculate the sum of strided array elements using an improved Kahan–Babuška algorithm.</span>
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- <spanclass="signature">[`gsumkbn2( N, x, strideX )`][@stdlib/blas/ext/base/gsumkbn2]</span><spanclass="delimiter">: </span><spanclass="description">calculate the sum of strided array elements using a second-order iterative Kahan–Babuška algorithm.</span>
Copy file name to clipboardExpand all lines: lib/node_modules/@stdlib/stats/base/README.md
+3-3Lines changed: 3 additions & 3 deletions
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@@ -89,7 +89,7 @@ The namespace contains the following statistical functions:
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- <spanclass="signature">[`dnanmax( N, x, strideX )`][@stdlib/stats/base/dnanmax]</span><spanclass="delimiter">: </span><spanclass="description">calculate the maximum value of a double-precision floating-point strided array, ignoring `NaN` values.</span>
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- <spanclass="signature">[`dnanmaxabs( N, x, strideX )`][@stdlib/stats/base/dnanmaxabs]</span><spanclass="delimiter">: </span><spanclass="description">calculate the maximum absolute value of a double-precision floating-point strided array, ignoring `NaN` values.</span>
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- <spanclass="signature">[`dnanmean( N, x, stride )`][@stdlib/stats/base/dnanmean]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values.</span>
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- <spanclass="signature">[`dnanmeanors( N, x, stride )`][@stdlib/stats/base/dnanmeanors]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using ordinary recursive summation.</span>
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- <spanclass="signature">[`dnanmeanors( N, x, strideX )`][@stdlib/stats/base/dnanmeanors]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using ordinary recursive summation.</span>
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- <spanclass="signature">[`dnanmeanpn( N, x, stride )`][@stdlib/stats/base/dnanmeanpn]</span><spanclass="delimiter">: </span><spanclass="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>
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- <spanclass="signature">[`dnanmeanpw( N, x, strideX )`][@stdlib/stats/base/dnanmeanpw]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using pairwise summation.</span>
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- <spanclass="signature">[`dnanmeanwd( N, x, strideX )`][@stdlib/stats/base/dnanmeanwd]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a double-precision floating-point strided array, using Welford's algorithm and ignoring `NaN` values.</span>
@@ -125,7 +125,7 @@ The namespace contains the following statistical functions:
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- <spanclass="signature">[`dsmeanwd( N, x, strideX )`][@stdlib/stats/base/dsmeanwd]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm with extended accumulation and returning an extended precision result.</span>
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- <spanclass="signature">[`dsnanmean( N, x, stride )`][@stdlib/stats/base/dsnanmean]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values, using extended accumulation, and returning an extended precision result.</span>
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- <spanclass="signature">[`dsnanmeanors( N, x, stride )`][@stdlib/stats/base/dsnanmeanors]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values, using ordinary recursive summation with extended accumulation, and returning an extended precision result.</span>
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- <spanclass="signature">[`dsnanmeanpn( N, x, stride )`][@stdlib/stats/base/dsnanmeanpn]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values, using a two-pass error correction algorithm with extended accumulation, and returning an extended precision result.</span>
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- <spanclass="signature">[`dsnanmeanpn( N, x, strideX )`][@stdlib/stats/base/dsnanmeanpn]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values, using a two-pass error correction algorithm with extended accumulation, and returning an extended precision result.</span>
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- <spanclass="signature">[`dsnanmeanwd( N, x, strideX )`][@stdlib/stats/base/dsnanmeanwd]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values, using Welford's algorithm with extended accumulation, and returning an extended precision result.</span>
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- <spanclass="signature">[`dstdev( N, correction, x, stride )`][@stdlib/stats/base/dstdev]</span><spanclass="delimiter">: </span><spanclass="description">calculate the standard deviation of a double-precision floating-point strided array.</span>
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- <spanclass="signature">[`dstdevch( N, correction, x, strideX )`][@stdlib/stats/base/dstdevch]</span><spanclass="delimiter">: </span><spanclass="description">calculate the standard deviation of a double-precision floating-point strided array using a one-pass trial mean algorithm.</span>
@@ -164,7 +164,7 @@ The namespace contains the following statistical functions:
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- <spanclass="signature">[`mskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/mskmin]</span><spanclass="delimiter">: </span><spanclass="description">calculate the minimum value of a strided array according to a mask.</span>
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- <spanclass="signature">[`mskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/mskrange]</span><spanclass="delimiter">: </span><spanclass="description">calculate the range of a strided array according to a mask.</span>
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- <spanclass="signature">[`nanmaxBy( N, x, stride, clbk[, thisArg] )`][@stdlib/stats/base/nanmax-by]</span><spanclass="delimiter">: </span><spanclass="description">calculate the maximum value of a strided array via a callback function, ignoring `NaN` values.</span>
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- <spanclass="signature">[`nanmax( N, x, stride )`][@stdlib/stats/base/nanmax]</span><spanclass="delimiter">: </span><spanclass="description">calculate the maximum value of a strided array, ignoring `NaN` values.</span>
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- <spanclass="signature">[`nanmax( N, x, strideX )`][@stdlib/stats/base/nanmax]</span><spanclass="delimiter">: </span><spanclass="description">calculate the maximum value of a strided array, ignoring `NaN` values.</span>
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- <spanclass="signature">[`nanmaxabs( N, x, stride )`][@stdlib/stats/base/nanmaxabs]</span><spanclass="delimiter">: </span><spanclass="description">calculate the maximum absolute value of a strided array, ignoring `NaN` values.</span>
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- <spanclass="signature">[`nanmean( N, x, stride )`][@stdlib/stats/base/nanmean]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a strided array, ignoring `NaN` values.</span>
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- <spanclass="signature">[`nanmeanors( N, x, stride )`][@stdlib/stats/base/nanmeanors]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a strided array, ignoring `NaN` values and using ordinary recursive summation.</span>
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