diff --git a/lib/node_modules/@stdlib/stats/base/README.md b/lib/node_modules/@stdlib/stats/base/README.md index 82af0eb1d162..31d6e65d23c4 100644 --- a/lib/node_modules/@stdlib/stats/base/README.md +++ b/lib/node_modules/@stdlib/stats/base/README.md @@ -66,23 +66,23 @@ The namespace contains the following statistical functions: - [`dmeanvar( N, correction, x, strideX, out, strideOut )`][@stdlib/stats/base/dmeanvar]: calculate the mean and variance of a double-precision floating-point strided array. - [`dmeanvarpn( N, correction, x, strideX, out, strideOut )`][@stdlib/stats/base/dmeanvarpn]: calculate the mean and variance of a double-precision floating-point strided array using a two-pass algorithm. - [`nanmean( N, x, strideX )`][@stdlib/stats/base/nanmean]: calculate the arithmetic mean of a strided array, ignoring `NaN` values. -- [`nanmeanors( N, x, stride )`][@stdlib/stats/base/nanmeanors]: calculate the arithmetic mean of a strided array, ignoring `NaN` values and using ordinary recursive summation. +- [`nanmeanors( N, x, strideX )`][@stdlib/stats/base/nanmeanors]: calculate the arithmetic mean of a strided array, ignoring `NaN` values and using ordinary recursive summation. - [`nanmeanpn( N, x, strideX )`][@stdlib/stats/base/nanmeanpn]: calculate the arithmetic mean of a strided array, ignoring `NaN` values and using a two-pass error correction algorithm. -- [`nanmeanwd( N, x, stride )`][@stdlib/stats/base/nanmeanwd]: calculate the arithmetic mean of a strided array, ignoring `NaN` values and using Welford's algorithm. +- [`nanmeanwd( N, x, strideX )`][@stdlib/stats/base/nanmeanwd]: calculate the arithmetic mean of a strided array, ignoring `NaN` values and using Welford's algorithm. - [`nanmskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/nanmskmax]: calculate the maximum value of a strided array according to a mask, ignoring `NaN` values. - [`nanmskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/nanmskmin]: calculate the minimum value of a strided array according to a mask, ignoring `NaN` values. - [`nanmskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/nanmskrange]: calculate the range of a strided array according to a mask, ignoring `NaN` values. - [`nanrangeBy( N, x, stride, clbk[, thisArg] )`][@stdlib/stats/base/nanrange-by]: calculate the range of a strided array via a callback function, ignoring `NaN` values. - [`nanrange( N, x, strideX )`][@stdlib/stats/base/nanrange]: calculate the range of a strided array, ignoring `NaN` values. -- [`nanstdev( N, correction, x, stride )`][@stdlib/stats/base/nanstdev]: calculate the standard deviation of a strided array ignoring `NaN` values. +- [`nanstdev( N, correction, x, strideX )`][@stdlib/stats/base/nanstdev]: calculate the standard deviation of a strided array ignoring `NaN` values. - [`nanstdevch( N, correction, x, stride )`][@stdlib/stats/base/nanstdevch]: calculate the standard deviation of a strided array ignoring `NaN` values and using a one-pass trial mean algorithm. -- [`nanstdevpn( N, correction, x, stride )`][@stdlib/stats/base/nanstdevpn]: calculate the standard deviation of a strided array ignoring `NaN` values and using a two-pass algorithm. +- [`nanstdevpn( N, correction, x, strideX )`][@stdlib/stats/base/nanstdevpn]: calculate the standard deviation of a strided array ignoring `NaN` values and using a two-pass algorithm. - [`nanstdevtk( N, correction, x, stride )`][@stdlib/stats/base/nanstdevtk]: calculate the standard deviation of a strided array ignoring `NaN` values and using a one-pass textbook algorithm. - [`nanstdevwd( N, correction, x, stride )`][@stdlib/stats/base/nanstdevwd]: calculate the standard deviation of a strided array ignoring `NaN` values and using Welford's algorithm. -- [`nanstdevyc( N, correction, x, stride )`][@stdlib/stats/base/nanstdevyc]: calculate the standard deviation of a strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer. -- [`nanvariance( N, correction, x, stride )`][@stdlib/stats/base/nanvariance]: calculate the variance of a strided array ignoring `NaN` values. +- [`nanstdevyc( N, correction, x, strideX )`][@stdlib/stats/base/nanstdevyc]: calculate the standard deviation of a strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer. +- [`nanvariance( N, correction, x, strideX )`][@stdlib/stats/base/nanvariance]: calculate the variance of a strided array ignoring `NaN` values. - [`nanvariancech( N, correction, x, strideX )`][@stdlib/stats/base/nanvariancech]: calculate the variance of a strided array ignoring `NaN` values and using a one-pass trial mean algorithm. -- [`nanvariancepn( N, correction, x, stride )`][@stdlib/stats/base/nanvariancepn]: calculate the variance of a strided array ignoring `NaN` values and using a two-pass algorithm. +- [`nanvariancepn( N, correction, x, strideX )`][@stdlib/stats/base/nanvariancepn]: calculate the variance of a strided array ignoring `NaN` values and using a two-pass algorithm. - [`nanvariancetk( N, correction, x, strideX )`][@stdlib/stats/base/nanvariancetk]: calculate the variance of a strided array ignoring `NaN` values and using a one-pass textbook algorithm. - [`nanvariancewd( N, correction, x, strideX )`][@stdlib/stats/base/nanvariancewd]: calculate the variance of a strided array ignoring `NaN` values and using Welford's algorithm. - [`nanvarianceyc( N, correction, x, strideX )`][@stdlib/stats/base/nanvarianceyc]: calculate the variance of a strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer. diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/README.md index e6f87e07fcd3..401461699c7d 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/README.md +++ b/lib/node_modules/@stdlib/stats/base/ndarray/README.md @@ -48,10 +48,12 @@ The namespace exposes the following APIs: - [`cumax( arrays )`][@stdlib/stats/base/ndarray/cumax]: compute the cumulative maximum value of a one-dimensional ndarray. - [`dcumax( arrays )`][@stdlib/stats/base/ndarray/dcumax]: compute the cumulative maximum value of a one-dimensional double-precision floating-point ndarray. - [`dmax( arrays )`][@stdlib/stats/base/ndarray/dmax]: compute the maximum value of a one-dimensional double-precision floating-point ndarray. +- [`dztest( arrays )`][@stdlib/stats/base/ndarray/dztest]: compute a one-sample Z-test for a one-dimensional double-precision floating-point ndarray. - [`maxBy( arrays, clbk[, thisArg ] )`][@stdlib/stats/base/ndarray/max-by]: compute the maximum value of a one-dimensional ndarray via a callback function. - [`max( arrays )`][@stdlib/stats/base/ndarray/max]: compute the maximum value of a one-dimensional ndarray. - [`scumax( arrays )`][@stdlib/stats/base/ndarray/scumax]: compute the cumulative maximum value of a one-dimensional single-precision floating-point ndarray. - [`smax( arrays )`][@stdlib/stats/base/ndarray/smax]: compute the maximum value of a one-dimensional single-precision floating-point ndarray. +- [`sztest( arrays )`][@stdlib/stats/base/ndarray/sztest]: compute a one-sample Z-test for a one-dimensional single-precision floating-point ndarray. @@ -100,6 +102,8 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/base/ndarray/dmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/dmax +[@stdlib/stats/base/ndarray/dztest]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/dztest + [@stdlib/stats/base/ndarray/max-by]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/max-by [@stdlib/stats/base/ndarray/max]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/max @@ -108,6 +112,8 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/base/ndarray/smax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/smax +[@stdlib/stats/base/ndarray/sztest]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/sztest +