diff --git a/lib/node_modules/@stdlib/stats/base/README.md b/lib/node_modules/@stdlib/stats/base/README.md index b0fb0ebfb3f8..4c24763dbda5 100644 --- a/lib/node_modules/@stdlib/stats/base/README.md +++ b/lib/node_modules/@stdlib/stats/base/README.md @@ -96,7 +96,7 @@ The namespace contains the following statistical functions: - [`dnanmeanors( N, x, stride )`][@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. - [`dnanmeanpw( N, x, stride )`][@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, stride )`][@stdlib/stats/base/dnanmeanwd]: calculate the arithmetic mean of a double-precision floating-point strided array, using Welford's algorithm and ignoring `NaN` values. +- [`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. - [`dnanminabs( N, x, strideX )`][@stdlib/stats/base/dnanminabs]: calculate the minimum absolute value of a double-precision floating-point strided array, ignoring `NaN` values. - [`dnanmskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/dnanmskmax]: calculate the maximum value of a double-precision floating-point strided array according to a mask, ignoring `NaN` values. @@ -217,11 +217,11 @@ The namespace contains the following statistical functions: - [`smeanpn( N, x, stride )`][@stdlib/stats/base/smeanpn]: calculate the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm. - [`smeanpw( N, x, stride )`][@stdlib/stats/base/smeanpw]: calculate the arithmetic mean of a single-precision floating-point strided array using pairwise summation. - [`smeanwd( N, x, stride )`][@stdlib/stats/base/smeanwd]: calculate the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm. -- [`smediansorted( N, x, stride )`][@stdlib/stats/base/smediansorted]: calculate the median value of a sorted single-precision floating-point strided array. +- [`smediansorted( N, x, strideX )`][@stdlib/stats/base/smediansorted]: calculate the median value of a sorted single-precision floating-point strided array. - [`smidrange( N, x, strideX )`][@stdlib/stats/base/smidrange]: calculate the mid-range of a single-precision floating-point strided array. - [`smin( N, x, strideX )`][@stdlib/stats/base/smin]: calculate the minimum value of a single-precision floating-point strided array. - [`sminabs( N, x, strideX )`][@stdlib/stats/base/sminabs]: calculate the minimum absolute value of a single-precision floating-point strided array. -- [`sminsorted( N, x, stride )`][@stdlib/stats/base/sminsorted]: calculate the minimum value of a sorted single-precision floating-point strided array. +- [`sminsorted( N, x, strideX )`][@stdlib/stats/base/sminsorted]: calculate the minimum value of a sorted single-precision floating-point strided array. - [`smskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/smskmax]: calculate the maximum value of a single-precision floating-point strided array according to a mask. - [`smskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/smskmin]: calculate the minimum value of a single-precision floating-point strided array according to a mask. - [`smskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/smskrange]: calculate the range of a single-precision floating-point strided array according to a mask.