From 946900d5c1f584b649157ac833ba19fac45bfc3d Mon Sep 17 00:00:00 2001 From: Planeshifter <1913638+Planeshifter@users.noreply.github.com> Date: Sat, 15 Feb 2025 02:35:52 +0000 Subject: [PATCH] docs: update namespace table of contents Signed-off-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com> --- lib/node_modules/@stdlib/stats/base/README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/lib/node_modules/@stdlib/stats/base/README.md b/lib/node_modules/@stdlib/stats/base/README.md index 84a9af577adc..35f84e79ff21 100644 --- a/lib/node_modules/@stdlib/stats/base/README.md +++ b/lib/node_modules/@stdlib/stats/base/README.md @@ -69,7 +69,7 @@ The namespace contains the following statistical functions: - [`dmeankbn( N, x, strideX )`][@stdlib/stats/base/dmeankbn]: calculate the arithmetic mean of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm. - [`dmeankbn2( N, x, strideX )`][@stdlib/stats/base/dmeankbn2]: calculate the arithmetic mean of a double-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm. - [`dmeanli( N, x, strideX )`][@stdlib/stats/base/dmeanli]: calculate the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm. -- [`dmeanlipw( N, x, stride )`][@stdlib/stats/base/dmeanlipw]: calculate the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm with pairwise summation. +- [`dmeanlipw( N, x, strideX )`][@stdlib/stats/base/dmeanlipw]: calculate the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm with pairwise summation. - [`dmeanors( N, x, strideX )`][@stdlib/stats/base/dmeanors]: calculate the arithmetic mean of a double-precision floating-point strided array using ordinary recursive summation. - [`dmeanpn( N, x, stride )`][@stdlib/stats/base/dmeanpn]: calculate the arithmetic mean of a double-precision floating-point strided array using a two-pass error correction algorithm. - [`dmeanpw( N, x, strideX )`][@stdlib/stats/base/dmeanpw]: calculate the arithmetic mean of a double-precision floating-point strided array using pairwise summation. @@ -90,7 +90,7 @@ The namespace contains the following statistical functions: - [`dnanmaxabs( N, x, strideX )`][@stdlib/stats/base/dnanmaxabs]: calculate the maximum absolute value of a double-precision floating-point strided array, ignoring `NaN` values. - [`dnanmean( N, x, stride )`][@stdlib/stats/base/dnanmean]: calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values. - [`dnanmeanors( N, x, strideX )`][@stdlib/stats/base/dnanmeanors]: calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using ordinary recursive summation. -- [`dnanmeanpn( N, x, stride )`][@stdlib/stats/base/dnanmeanpn]: calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using a two-pass error correction algorithm. +- [`dnanmeanpn( N, x, strideX )`][@stdlib/stats/base/dnanmeanpn]: calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using a two-pass error correction algorithm. - [`dnanmeanpw( N, x, strideX )`][@stdlib/stats/base/dnanmeanpw]: calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using pairwise summation. - [`dnanmeanwd( N, x, strideX )`][@stdlib/stats/base/dnanmeanwd]: calculate the arithmetic mean of a double-precision floating-point strided array, using Welford's algorithm and ignoring `NaN` values. - [`dnanmin( N, x, strideX )`][@stdlib/stats/base/dnanmin]: calculate the minimum value of a double-precision floating-point strided array, ignoring `NaN` values. @@ -124,7 +124,7 @@ The namespace contains the following statistical functions: - [`dsmeanpw( N, x, strideX )`][@stdlib/stats/base/dsmeanpw]: calculate the arithmetic mean of a single-precision floating-point strided array using pairwise summation with extended accumulation and returning an extended precision result. - [`dsmeanwd( N, x, strideX )`][@stdlib/stats/base/dsmeanwd]: 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. - [`dsnanmean( N, x, stride )`][@stdlib/stats/base/dsnanmean]: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values, using extended accumulation, and returning an extended precision result. -- [`dsnanmeanors( N, x, stride )`][@stdlib/stats/base/dsnanmeanors]: 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. +- [`dsnanmeanors( N, x, strideX )`][@stdlib/stats/base/dsnanmeanors]: 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. - [`dsnanmeanpn( N, x, strideX )`][@stdlib/stats/base/dsnanmeanpn]: 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. - [`dsnanmeanwd( N, x, strideX )`][@stdlib/stats/base/dsnanmeanwd]: 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. - [`dstdev( N, correction, x, stride )`][@stdlib/stats/base/dstdev]: calculate the standard deviation of a double-precision floating-point strided array.