stats-strided

Statistical operations for strided arrays.

https://github.com/stdlib-js/stats-strided

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Keywords

array javascript namespace ndarray node node-js nodejs statistics stats stdlib strided vector

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Statistical operations for strided arrays.

Basic Info

Host: GitHub
Owner: stdlib-js
License: apache-2.0
Language: JavaScript
Default Branch: main
Homepage: https://github.com/stdlib-js/stdlib
Size: 228 KB

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array javascript namespace ndarray node node-js nodejs statistics stats stdlib strided vector

Created 9 months ago · Last pushed 6 months ago

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We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.

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Statistics

Statistical operations for strided arrays.

## Installation ```bash npm install @stdlib/stats-strided ``` Alternatively, - To load the package in a website via a `script` tag without installation and bundlers, use the [ES Module][es-module] available on the [`esm`][esm-url] branch (see [README][esm-readme]). - If you are using Deno, visit the [`deno`][deno-url] branch (see [README][deno-readme] for usage intructions). - For use in Observable, or in browser/node environments, use the [Universal Module Definition (UMD)][umd] build available on the [`umd`][umd-url] branch (see [README][umd-readme]). The [branches.md][branches-url] file summarizes the available branches and displays a diagram illustrating their relationships. To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.

## Usage ```javascript var ns = require( '@stdlib/stats-strided' ); ``` #### ns Namespace containing APIs for performing statistical operations on strided arrays. ```javascript var o = ns; // returns {...} ``` The namespace exports the following:

- [`dcumax( N, x, strideX, y, strideY )`][@stdlib/stats/strided/dcumax]: calculate the cumulative maximum of double-precision floating-point strided array elements. - [`dcumaxabs( N, x, strideX, y, strideY )`][@stdlib/stats/strided/dcumaxabs]: calculate the cumulative maximum absolute value of double-precision floating-point strided array elements. - [`dcumin( N, x, strideX, y, strideY )`][@stdlib/stats/strided/dcumin]: calculate the cumulative minimum of double-precision floating-point strided array elements. - [`dcuminabs( N, x, strideX, y, strideY )`][@stdlib/stats/strided/dcuminabs]: calculate the cumulative minimum absolute value of double-precision floating-point strided array elements. - [`dmax( N, x, strideX )`][@stdlib/stats/strided/dmax]: calculate the maximum value of a double-precision floating-point strided array. - [`dmaxabs( N, x, strideX )`][@stdlib/stats/strided/dmaxabs]: calculate the maximum absolute value of a double-precision floating-point strided array. - [`dmaxabssorted( N, x, strideX )`][@stdlib/stats/strided/dmaxabssorted]: calculate the maximum absolute value of a sorted double-precision floating-point strided array. - [`dmaxsorted( N, x, strideX )`][@stdlib/stats/strided/dmaxsorted]: calculate the maximum value of a sorted double-precision floating-point strided array. - [`dmean( N, x, strideX )`][@stdlib/stats/strided/dmean]: calculate the arithmetic mean of a double-precision floating-point strided array. - [`dmeankbn( N, x, strideX )`][@stdlib/stats/strided/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/strided/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/strided/dmeanli]: calculate the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm. - [`dmeanlipw( N, x, strideX )`][@stdlib/stats/strided/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/strided/dmeanors]: calculate the arithmetic mean of a double-precision floating-point strided array using ordinary recursive summation. - [`dmeanpn( N, x, strideX )`][@stdlib/stats/strided/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/strided/dmeanpw]: calculate the arithmetic mean of a double-precision floating-point strided array using pairwise summation. - [`dmeanwd( N, x, strideX )`][@stdlib/stats/strided/dmeanwd]: calculate the arithmetic mean of a double-precision floating-point strided array using Welford's algorithm. - [`dmediansorted( N, x, strideX )`][@stdlib/stats/strided/dmediansorted]: calculate the median value of a sorted double-precision floating-point strided array. - [`dmidrange( N, x, strideX )`][@stdlib/stats/strided/dmidrange]: calculate the mid-range of a double-precision floating-point strided array. - [`dmin( N, x, strideX )`][@stdlib/stats/strided/dmin]: calculate the minimum value of a double-precision floating-point strided array. - [`dminabs( N, x, strideX )`][@stdlib/stats/strided/dminabs]: calculate the minimum absolute value of a double-precision floating-point strided array. - [`dminsorted( N, x, strideX )`][@stdlib/stats/strided/dminsorted]: calculate the minimum value of a sorted double-precision floating-point strided array. - [`dmskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dmskmax]: calculate the maximum value of a double-precision floating-point strided array according to a mask. - [`dmskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dmskmin]: calculate the minimum value of a double-precision floating-point strided array according to a mask. - [`dmskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dmskrange]: calculate the range of a double-precision floating-point strided array according to a mask. - [`dnanmax( N, x, strideX )`][@stdlib/stats/strided/dnanmax]: calculate the maximum value of a double-precision floating-point strided array, ignoring `NaN` values. - [`dnanmaxabs( N, x, strideX )`][@stdlib/stats/strided/dnanmaxabs]: calculate the maximum absolute value of a double-precision floating-point strided array, ignoring `NaN` values. - [`dnanmean( N, x, strideX )`][@stdlib/stats/strided/dnanmean]: calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values. - [`dnanmeanors( N, x, strideX )`][@stdlib/stats/strided/dnanmeanors]: calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using ordinary recursive summation. - [`dnanmeanpn( N, x, strideX )`][@stdlib/stats/strided/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/strided/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/strided/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/strided/dnanmin]: calculate the minimum value of a double-precision floating-point strided array, ignoring `NaN` values. - [`dnanminabs( N, x, strideX )`][@stdlib/stats/strided/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/strided/dnanmskmax]: calculate the maximum value of a double-precision floating-point strided array according to a mask, ignoring `NaN` values. - [`dnanmskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dnanmskmin]: calculate the minimum value of a double-precision floating-point strided array according to a mask, ignoring `NaN` values. - [`dnanmskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dnanmskrange]: calculate the range of a double-precision floating-point strided array according to a mask, ignoring `NaN` values. - [`dnanrange( N, x, strideX )`][@stdlib/stats/strided/dnanrange]: calculate the range of a double-precision floating-point strided array, ignoring `NaN` values. - [`dnanstdev( N, correction, x, strideX )`][@stdlib/stats/strided/dnanstdev]: calculate the standard deviation of a double-precision floating-point strided array ignoring `NaN` values. - [`dnanstdevch( N, correction, x, strideX )`][@stdlib/stats/strided/dnanstdevch]: calculate the standard deviation of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass trial mean algorithm. - [`dnanstdevpn( N, correction, x, strideX )`][@stdlib/stats/strided/dnanstdevpn]: calculate the standard deviation of a double-precision floating-point strided array, ignoring `NaN` values and using a two-pass algorithm. - [`dnanstdevtk( N, correction, x, strideX )`][@stdlib/stats/strided/dnanstdevtk]: calculate the standard deviation of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass textbook algorithm. - [`dnanstdevwd( N, correction, x, strideX )`][@stdlib/stats/strided/dnanstdevwd]: calculate the standard deviation of a double-precision floating-point strided array ignoring `NaN` values and using Welford's algorithm. - [`dnanstdevyc( N, correction, x, strideX )`][@stdlib/stats/strided/dnanstdevyc]: calculate the standard deviation of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer. - [`dnanvariance( N, correction, x, strideX )`][@stdlib/stats/strided/dnanvariance]: calculate the variance of a double-precision floating-point strided array ignoring `NaN` values. - [`dnanvariancech( N, correction, x, strideX )`][@stdlib/stats/strided/dnanvariancech]: calculate the variance of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass trial mean algorithm. - [`dnanvariancepn( N, correction, x, strideX )`][@stdlib/stats/strided/dnanvariancepn]: calculate the variance of a double-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm. - [`dnanvariancetk( N, correction, x, strideX )`][@stdlib/stats/strided/dnanvariancetk]: calculate the variance of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass textbook algorithm. - [`dnanvariancewd( N, correction, x, strideX )`][@stdlib/stats/strided/dnanvariancewd]: calculate the variance of a double-precision floating-point strided array ignoring `NaN` values and using Welford's algorithm. - [`dnanvarianceyc( N, correction, x, strideX )`][@stdlib/stats/strided/dnanvarianceyc]: calculate the variance of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer. - [`drange( N, x, strideX )`][@stdlib/stats/strided/drange]: calculate the range of a double-precision floating-point strided array. - [`dsem( N, correction, x, strideX )`][@stdlib/stats/strided/dsem]: calculate the standard error of the mean of a double-precision floating-point strided array. - [`dsemch( N, correction, x, strideX )`][@stdlib/stats/strided/dsemch]: calculate the standard error of the mean of a double-precision floating-point strided array using a one-pass trial mean algorithm. - [`dsempn( N, correction, x, strideX )`][@stdlib/stats/strided/dsempn]: calculate the standard error of the mean of a double-precision floating-point strided array using a two-pass algorithm. - [`dsemtk( N, correction, x, strideX )`][@stdlib/stats/strided/dsemtk]: calculate the standard error of the mean of a double-precision floating-point strided array using a one-pass textbook algorithm. - [`dsemwd( N, correction, x, strideX )`][@stdlib/stats/strided/dsemwd]: calculate the standard error of the mean of a double-precision floating-point strided array using Welford's algorithm. - [`dsemyc( N, correction, x, strideX )`][@stdlib/stats/strided/dsemyc]: calculate the standard error of the mean of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. - [`dsmean( N, x, strideX )`][@stdlib/stats/strided/dsmean]: calculate the arithmetic mean of a single-precision floating-point strided array using extended accumulation and returning an extended precision result. - [`dsmeanors( N, x, strideX )`][@stdlib/stats/strided/dsmeanors]: calculate the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and returning an extended precision result. - [`dsmeanpn( N, x, strideX )`][@stdlib/stats/strided/dsmeanpn]: calculate the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and returning an extended precision result. - [`dsmeanpw( N, x, strideX )`][@stdlib/stats/strided/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/strided/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, strideX )`][@stdlib/stats/strided/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, strideX )`][@stdlib/stats/strided/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/strided/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/strided/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, strideX )`][@stdlib/stats/strided/dstdev]: calculate the standard deviation of a double-precision floating-point strided array. - [`dstdevch( N, correction, x, strideX )`][@stdlib/stats/strided/dstdevch]: calculate the standard deviation of a double-precision floating-point strided array using a one-pass trial mean algorithm. - [`dstdevpn( N, correction, x, strideX )`][@stdlib/stats/strided/dstdevpn]: calculate the standard deviation of a double-precision floating-point strided array using a two-pass algorithm. - [`dstdevtk( N, correction, x, strideX )`][@stdlib/stats/strided/dstdevtk]: calculate the standard deviation of a double-precision floating-point strided array using a one-pass textbook algorithm. - [`dstdevwd( N, correction, x, strideX )`][@stdlib/stats/strided/dstdevwd]: calculate the standard deviation of a double-precision floating-point strided array using Welford's algorithm. - [`dstdevyc( N, correction, x, strideX )`][@stdlib/stats/strided/dstdevyc]: calculate the standard deviation of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. - [`dsvariance( N, correction, x, strideX )`][@stdlib/stats/strided/dsvariance]: calculate the variance of a single-precision floating-point strided array using extended accumulation and returning an extended precision result. - [`dsvariancepn( N, correction, x, strideX )`][@stdlib/stats/strided/dsvariancepn]: calculate the variance of a single-precision floating-point strided array using a two-pass algorithm with extended accumulation and returning an extended precision result. - [`dvariance( N, correction, x, strideX )`][@stdlib/stats/strided/dvariance]: calculate the variance of a double-precision floating-point strided array. - [`dvariancech( N, correction, x, strideX )`][@stdlib/stats/strided/dvariancech]: calculate the variance of a double-precision floating-point strided array using a one-pass trial mean algorithm. - [`dvariancepn( N, correction, x, strideX )`][@stdlib/stats/strided/dvariancepn]: calculate the variance of a double-precision floating-point strided array using a two-pass algorithm. - [`dvariancetk( N, correction, x, strideX )`][@stdlib/stats/strided/dvariancetk]: calculate the variance of a double-precision floating-point strided array using a one-pass textbook algorithm. - [`dvariancewd( N, correction, x, strideX )`][@stdlib/stats/strided/dvariancewd]: calculate the variance of a double-precision floating-point strided array using Welford's algorithm. - [`dvarianceyc( N, correction, x, strideX )`][@stdlib/stats/strided/dvarianceyc]: calculate the variance of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. - [`dvarm( N, mean, correction, x, strideX )`][@stdlib/stats/strided/dvarm]: calculate the variance of a double-precision floating-point strided array provided a known mean. - [`dvarmpn( N, mean, correction, x, strideX )`][@stdlib/stats/strided/dvarmpn]: calculate the variance of a double-precision floating-point strided array provided a known mean and using Neely's correction algorithm. - [`dvarmtk( N, mean, correction, x, strideX )`][@stdlib/stats/strided/dvarmtk]: calculate the variance of a double-precision floating-point strided array provided a known mean and using a one-pass textbook algorithm. - [`dztest( N, alternative, alpha, mu, sigma, x, strideX, out )`][@stdlib/stats/strided/dztest]: compute a one-sample Z-test for a double-precision floating-point strided array. - [`maxBy( N, x, strideX, clbk[, thisArg] )`][@stdlib/stats/strided/max-by]: calculate the maximum value of a strided array via a callback function. - [`max( N, x, strideX )`][@stdlib/stats/strided/max]: calculate the maximum value of a strided array. - [`maxabs( N, x, strideX )`][@stdlib/stats/strided/maxabs]: calculate the maximum absolute value of a strided array. - [`maxsorted( N, x, strideX )`][@stdlib/stats/strided/maxsorted]: calculate the maximum value of a sorted strided array. - [`mean( N, x, strideX )`][@stdlib/stats/strided/mean]: calculate the arithmetic mean of a strided array. - [`meankbn( N, x, strideX )`][@stdlib/stats/strided/meankbn]: calculate the arithmetic mean of a strided array using an improved Kahan–Babuška algorithm. - [`meankbn2( N, x, strideX )`][@stdlib/stats/strided/meankbn2]: calculate the arithmetic mean of a strided array using a second-order iterative Kahan–Babuška algorithm. - [`meanors( N, x, strideX )`][@stdlib/stats/strided/meanors]: calculate the arithmetic mean of a strided array using ordinary recursive summation. - [`meanpn( N, x, strideX )`][@stdlib/stats/strided/meanpn]: calculate the arithmetic mean of a strided array using a two-pass error correction algorithm. - [`meanpw( N, x, strideX )`][@stdlib/stats/strided/meanpw]: calculate the arithmetic mean of a strided array using pairwise summation. - [`meanwd( N, x, strideX )`][@stdlib/stats/strided/meanwd]: calculate the arithmetic mean of a strided array using Welford's algorithm. - [`mediansorted( N, x, strideX )`][@stdlib/stats/strided/mediansorted]: calculate the median value of a sorted strided array. - [`minBy( N, x, strideX, clbk[, thisArg] )`][@stdlib/stats/strided/min-by]: calculate the minimum value of a strided array via a callback function. - [`min( N, x, strideX )`][@stdlib/stats/strided/min]: calculate the minimum value of a strided array. - [`minabs( N, x, strideX )`][@stdlib/stats/strided/minabs]: calculate the minimum absolute value of a strided array. - [`minsorted( N, x, strideX )`][@stdlib/stats/strided/minsorted]: calculate the minimum value of a sorted strided array. - [`mskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/mskmax]: calculate the maximum value of a strided array according to a mask. - [`mskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/mskmin]: calculate the minimum value of a strided array according to a mask. - [`mskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/mskrange]: calculate the range of a strided array according to a mask. - [`nanmaxBy( N, x, strideX, clbk[, thisArg] )`][@stdlib/stats/strided/nanmax-by]: calculate the maximum value of a strided array via a callback function, ignoring `NaN` values. - [`nanmax( N, x, strideX )`][@stdlib/stats/strided/nanmax]: calculate the maximum value of a strided array, ignoring `NaN` values. - [`nanmaxabs( N, x, strideX )`][@stdlib/stats/strided/nanmaxabs]: calculate the maximum absolute value of a strided array, ignoring `NaN` values. - [`nanminBy( N, x, strideX, clbk[, thisArg] )`][@stdlib/stats/strided/nanmin-by]: calculate the minimum value of a strided array via a callback function, ignoring `NaN` values. - [`nanmin( N, x, strideX )`][@stdlib/stats/strided/nanmin]: calculate the minimum value of a strided array, ignoring `NaN` values. - [`nanminabs( N, x, strideX )`][@stdlib/stats/strided/nanminabs]: calculate the minimum absolute value of a strided array, ignoring `NaN` values. - [`scumax( N, x, strideX, y, strideY )`][@stdlib/stats/strided/scumax]: calculate the cumulative maximum of single-precision floating-point strided array elements. - [`scumaxabs( N, x, strideX, y, strideY )`][@stdlib/stats/strided/scumaxabs]: calculate the cumulative maximum absolute value of single-precision floating-point strided array elements. - [`scumin( N, x, strideX, y, strideY )`][@stdlib/stats/strided/scumin]: calculate the cumulative minimum of single-precision floating-point strided array elements. - [`scuminabs( N, x, strideX, y, strideY )`][@stdlib/stats/strided/scuminabs]: calculate the cumulative minimum absolute value of single-precision floating-point strided array elements. - [`sdsmean( N, x, strideX )`][@stdlib/stats/strided/sdsmean]: calculate the arithmetic mean of a single-precision floating-point strided array using extended accumulation. - [`sdsmeanors( N, x, strideX )`][@stdlib/stats/strided/sdsmeanors]: calculate the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation. - [`smax( N, x, strideX )`][@stdlib/stats/strided/smax]: calculate the maximum value of a single-precision floating-point strided array. - [`smaxabs( N, x, strideX )`][@stdlib/stats/strided/smaxabs]: calculate the maximum absolute value of a single-precision floating-point strided array. - [`smaxabssorted( N, x, strideX )`][@stdlib/stats/strided/smaxabssorted]: calculate the maximum absolute value of a sorted single-precision floating-point strided array. - [`smaxsorted( N, x, stride )`][@stdlib/stats/strided/smaxsorted]: calculate the maximum value of a sorted single-precision floating-point strided array. - [`smean( N, x, strideX )`][@stdlib/stats/strided/smean]: calculate the arithmetic mean of a single-precision floating-point strided array. - [`smeanli( N, x, strideX )`][@stdlib/stats/strided/smeanli]: calculate the arithmetic mean of a single-precision floating-point strided array using a one-pass trial mean algorithm. - [`smeanpn( N, x, strideX )`][@stdlib/stats/strided/smeanpn]: calculate the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm. - [`smeanpw( N, x, strideX )`][@stdlib/stats/strided/smeanpw]: calculate the arithmetic mean of a single-precision floating-point strided array using pairwise summation. - [`smeanwd( N, x, strideX )`][@stdlib/stats/strided/smeanwd]: calculate the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm. - [`smediansorted( N, x, strideX )`][@stdlib/stats/strided/smediansorted]: calculate the median value of a sorted single-precision floating-point strided array. - [`smidrange( N, x, strideX )`][@stdlib/stats/strided/smidrange]: calculate the mid-range of a single-precision floating-point strided array. - [`smin( N, x, strideX )`][@stdlib/stats/strided/smin]: calculate the minimum value of a single-precision floating-point strided array. - [`sminabs( N, x, strideX )`][@stdlib/stats/strided/sminabs]: calculate the minimum absolute value of a single-precision floating-point strided array. - [`sminsorted( N, x, strideX )`][@stdlib/stats/strided/sminsorted]: calculate the minimum value of a sorted single-precision floating-point strided array. - [`smskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/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/strided/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/strided/smskrange]: calculate the range of a single-precision floating-point strided array according to a mask. - [`snanmax( N, x, strideX )`][@stdlib/stats/strided/snanmax]: calculate the maximum value of a single-precision floating-point strided array, ignoring `NaN` values. - [`snanmaxabs( N, x, strideX )`][@stdlib/stats/strided/snanmaxabs]: calculate the maximum absolute value of a single-precision floating-point strided array, ignoring `NaN` values. - [`snanmeanors( N, x, strideX )`][@stdlib/stats/strided/snanmeanors]: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using ordinary recursive summation. - [`snanmeanpn( N, x, strideX )`][@stdlib/stats/strided/snanmeanpn]: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using a two-pass error correction algorithm. - [`snanmeanwd( N, x, strideX )`][@stdlib/stats/strided/snanmeanwd]: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using Welford's algorithm. - [`snanmin( N, x, strideX )`][@stdlib/stats/strided/snanmin]: calculate the minimum value of a single-precision floating-point strided array, ignoring `NaN` values. - [`snanminabs( N, x, strideX )`][@stdlib/stats/strided/snanminabs]: calculate the minimum absolute value of a single-precision floating-point strided array, ignoring `NaN` values. - [`snanmskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/snanmskmax]: calculate the maximum value of a single-precision floating-point strided array according to a mask, ignoring `NaN` values. - [`snanmskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/snanmskmin]: calculate the minimum value of a single-precision floating-point strided array according to a mask, ignoring `NaN` values. - [`snanmskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/snanmskrange]: calculate the range of a single-precision floating-point strided array according to a mask, ignoring `NaN` values. - [`snanrange( N, x, strideX )`][@stdlib/stats/strided/snanrange]: calculate the range of a single-precision floating-point strided array, ignoring `NaN` values. - [`srange( N, x, strideX )`][@stdlib/stats/strided/srange]: calculate the range of a single-precision floating-point strided array. - [`sstdev( N, correction, x, strideX )`][@stdlib/stats/strided/sstdev]: calculate the standard deviation of a single-precision floating-point strided array. - [`sstdevch( N, correction, x, strideX )`][@stdlib/stats/strided/sstdevch]: calculate the standard deviation of a single-precision floating-point strided array using a one-pass trial mean algorithm. - [`sstdevpn( N, correction, x, strideX )`][@stdlib/stats/strided/sstdevpn]: calculate the standard deviation of a single-precision floating-point strided array using a two-pass algorithm. - [`sstdevtk( N, correction, x, strideX )`][@stdlib/stats/strided/sstdevtk]: calculate the standard deviation of a single-precision floating-point strided array using a one-pass textbook algorithm. - [`sstdevyc( N, correction, x, strideX )`][@stdlib/stats/strided/sstdevyc]: calculate the standard deviation of a single-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. - [`svariancech( N, correction, x, strideX )`][@stdlib/stats/strided/svariancech]: calculate the variance of a single-precision floating-point strided array using a one-pass trial mean algorithm. - [`svariancepn( N, correction, x, strideX )`][@stdlib/stats/strided/svariancepn]: calculate the variance of a single-precision floating-point strided array using a two-pass algorithm. - [`svariancetk( N, correction, x, strideX )`][@stdlib/stats/strided/svariancetk]: calculate the variance of a single-precision floating-point strided array using a one-pass textbook algorithm. - [`svarianceyc( N, correction, x, strideX )`][@stdlib/stats/strided/svarianceyc]: calculate the variance of a single-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. - [`sztest( N, alternative, alpha, mu, sigma, x, strideX, out )`][@stdlib/stats/strided/sztest]: compute a one-sample Z-test for a single-precision floating-point strided array. - [`ztest( N, alternative, alpha, mu, sigma, x, strideX, out )`][@stdlib/stats/strided/ztest]: compute a one-sample Z-test for a strided array.

## Examples ```javascript var objectKeys = require( '@stdlib/utils-keys' ); var ns = require( '@stdlib/stats-strided' ); console.log( objectKeys( ns ) ); ```

* * * ## Notice This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib]. #### Community [![Chat][chat-image]][chat-url] --- ## License See [LICENSE][stdlib-license]. ## Copyright Copyright © 2016-2025. The Stdlib [Authors][stdlib-authors].

Owner

Name: stdlib
Login: stdlib-js
Kind: organization

Website: https://stdlib.io
Twitter: stdlibjs
Repositories: 3,692
Profile: https://github.com/stdlib-js

Standard library for JavaScript.

Citation (CITATION.cff)

cff-version: 1.2.0
title: stdlib
message: >-
  If you use this software, please cite it using the
  metadata from this file.

type: software

authors:
  - name: The Stdlib Authors
    url: https://github.com/stdlib-js/stdlib/graphs/contributors

repository-code: https://github.com/stdlib-js/stdlib
url: https://stdlib.io

abstract: |
  Standard library for JavaScript and Node.js.

keywords:
  - JavaScript
  - Node.js
  - TypeScript
  - standard library
  - scientific computing
  - numerical computing
  - statistical computing

license: Apache-2.0 AND BSL-1.0

date-released: 2016

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@stdlib/stats-strided-snanminabs github:stdlib-js/stats-strided-snanminabs#main
@stdlib/stats-strided-snanmskmax github:stdlib-js/stats-strided-snanmskmax#main
@stdlib/stats-strided-snanmskmin github:stdlib-js/stats-strided-snanmskmin#main
@stdlib/stats-strided-snanmskrange github:stdlib-js/stats-strided-snanmskrange#main
@stdlib/stats-strided-snanrange github:stdlib-js/stats-strided-snanrange#main
@stdlib/stats-strided-srange github:stdlib-js/stats-strided-srange#main
@stdlib/stats-strided-sstdevch github:stdlib-js/stats-strided-sstdevch#main
@stdlib/stats-strided-sstdevpn github:stdlib-js/stats-strided-sstdevpn#main
@stdlib/stats-strided-sstdevtk github:stdlib-js/stats-strided-sstdevtk#main
@stdlib/stats-strided-sstdevyc github:stdlib-js/stats-strided-sstdevyc#main
@stdlib/stats-strided-svariancech github:stdlib-js/stats-strided-svariancech#main
@stdlib/stats-strided-svariancepn github:stdlib-js/stats-strided-svariancepn#main
@stdlib/stats-strided-svariancetk github:stdlib-js/stats-strided-svariancetk#main
@stdlib/stats-strided-svarianceyc github:stdlib-js/stats-strided-svarianceyc#main
@stdlib/utils-define-read-only-property ^0.2.2

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