diff --git a/lib/node_modules/@stdlib/blas/base/README.md b/lib/node_modules/@stdlib/blas/base/README.md index 9cdbd9445f4f..f7dc7f2fb1ad 100644 --- a/lib/node_modules/@stdlib/blas/base/README.md +++ b/lib/node_modules/@stdlib/blas/base/README.md @@ -88,7 +88,7 @@ var o = blas; - [`zaxpy( N, alpha, x, strideX, y, strideY )`][@stdlib/blas/base/zaxpy]: scale a double-precision complex floating-point vector by a double-precision complex floating-point constant and add the result to a double-precision complex floating-point vector. - [`zcopy( N, x, strideX, y, strideY )`][@stdlib/blas/base/zcopy]: copy values from one complex double-precision floating-point vector to another complex double-precision floating-point vector. - [`zdrot( N, x, strideX, y, strideY, c, s )`][@stdlib/blas/base/zdrot]: apply a plane rotation. -- [`zdscal( N, da, zx, strideZX )`][@stdlib/blas/base/zdscal]: scale a double-precision complex floating-point vector by a double-precision floating-point constant. +- [`zdscal( N, alpha, x, strideX )`][@stdlib/blas/base/zdscal]: scale a double-precision complex floating-point vector by a double-precision floating-point constant. - [`zscal( N, alpha, x, strideX )`][@stdlib/blas/base/zscal]: scales a double-precision complex floating-point vector by a double-precision complex floating-point constant. - [`zswap( N, x, strideX, y, strideY )`][@stdlib/blas/base/zswap]: interchange two complex double-precision floating-point vectors. diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/README.md b/lib/node_modules/@stdlib/ndarray/base/assert/README.md index 97d217ad2608..cf0c54543266 100644 --- a/lib/node_modules/@stdlib/ndarray/base/assert/README.md +++ b/lib/node_modules/@stdlib/ndarray/base/assert/README.md @@ -78,6 +78,7 @@ var o = ns; - [`isScalarMostlySafeCompatible( value, dtype )`][@stdlib/ndarray/base/assert/is-scalar-mostly-safe-compatible]: determine whether a scalar value can be safely cast or, for floating-point data types, downcast to specified ndarray data type. - [`isSignedIntegerDataType( value )`][@stdlib/ndarray/base/assert/is-signed-integer-data-type]: test if an input value is a supported ndarray signed integer data type. - [`isSingleSegmentCompatible( shape, strides, offset )`][@stdlib/ndarray/base/assert/is-single-segment-compatible]: determine if an array is compatible with a single memory segment. +- [`isStructDataType( value )`][@stdlib/ndarray/base/assert/is-struct-data-type]: test if an input value is a supported ndarray struct data type. - [`isUnsignedIntegerDataType( value )`][@stdlib/ndarray/base/assert/is-unsigned-integer-data-type]: test if an input value is a supported ndarray unsigned integer data type. @@ -191,6 +192,8 @@ console.log( objectKeys( ns ) ); [@stdlib/ndarray/base/assert/is-single-segment-compatible]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/assert/is-single-segment-compatible +[@stdlib/ndarray/base/assert/is-struct-data-type]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/assert/is-struct-data-type + [@stdlib/ndarray/base/assert/is-unsigned-integer-data-type]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/assert/is-unsigned-integer-data-type diff --git a/lib/node_modules/@stdlib/stats/base/README.md b/lib/node_modules/@stdlib/stats/base/README.md index bab914afffb8..02760a63de17 100644 --- a/lib/node_modules/@stdlib/stats/base/README.md +++ b/lib/node_modules/@stdlib/stats/base/README.md @@ -115,7 +115,7 @@ The namespace contains the following statistical functions: - [`stdevtk( N, correction, x, stride )`][@stdlib/stats/base/stdevtk]: calculate the standard deviation of a strided array using a one-pass textbook algorithm. - [`stdevwd( N, correction, x, stride )`][@stdlib/stats/base/stdevwd]: calculate the standard deviation of a strided array using Welford's algorithm. - [`stdevyc( N, correction, x, stride )`][@stdlib/stats/base/stdevyc]: calculate the standard deviation of a strided array using a one-pass algorithm proposed by Youngs and Cramer. -- [`svariance( N, correction, x, stride )`][@stdlib/stats/base/svariance]: calculate the variance of a single-precision floating-point strided array. +- [`svariance( N, correction, x, strideX )`][@stdlib/stats/base/svariance]: calculate the variance of a single-precision floating-point strided array. - [`svariancewd( N, correction, x, strideX )`][@stdlib/stats/base/svariancewd]: calculate the variance of a single-precision floating-point strided array using Welford's algorithm. - [`variance( N, correction, x, stride )`][@stdlib/stats/base/variance]: calculate the variance of a strided array. - [`variancech( N, correction, x, strideX )`][@stdlib/stats/base/variancech]: calculate the variance of a strided array using a one-pass trial mean algorithm. diff --git a/lib/node_modules/@stdlib/stats/strided/README.md b/lib/node_modules/@stdlib/stats/strided/README.md index 8008935991eb..cf3c79856330 100644 --- a/lib/node_modules/@stdlib/stats/strided/README.md +++ b/lib/node_modules/@stdlib/stats/strided/README.md @@ -135,7 +135,35 @@ The namespace exports the following: - [`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. @@ -146,7 +174,9 @@ The namespace exports the following: - [`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. @@ -169,6 +199,7 @@ The namespace exports the following: - [`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. @@ -177,6 +208,8 @@ The namespace exports the following: - [`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. @@ -389,8 +422,64 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/strided/dvarianceyc]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dvarianceyc +[@stdlib/stats/strided/dvarm]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dvarm + +[@stdlib/stats/strided/dvarmpn]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dvarmpn + [@stdlib/stats/strided/dvarmtk]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dvarmtk +[@stdlib/stats/strided/dztest]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dztest + +[@stdlib/stats/strided/max-by]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/max-by + +[@stdlib/stats/strided/max]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/max + +[@stdlib/stats/strided/maxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/maxabs + +[@stdlib/stats/strided/maxsorted]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/maxsorted + +[@stdlib/stats/strided/mean]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/mean + +[@stdlib/stats/strided/meankbn]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/meankbn + +[@stdlib/stats/strided/meankbn2]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/meankbn2 + +[@stdlib/stats/strided/meanors]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/meanors + +[@stdlib/stats/strided/meanpn]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/meanpn + +[@stdlib/stats/strided/meanpw]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/meanpw + +[@stdlib/stats/strided/meanwd]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/meanwd + +[@stdlib/stats/strided/mediansorted]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/mediansorted + +[@stdlib/stats/strided/min-by]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/min-by + +[@stdlib/stats/strided/min]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/min + +[@stdlib/stats/strided/minabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/minabs + +[@stdlib/stats/strided/minsorted]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/minsorted + +[@stdlib/stats/strided/mskmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/mskmax + +[@stdlib/stats/strided/mskmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/mskmin + +[@stdlib/stats/strided/mskrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/mskrange + +[@stdlib/stats/strided/nanmax-by]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanmax-by + +[@stdlib/stats/strided/nanmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanmax + +[@stdlib/stats/strided/nanmaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanmaxabs + +[@stdlib/stats/strided/nanmin-by]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanmin-by + +[@stdlib/stats/strided/nanmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanmin + +[@stdlib/stats/strided/nanminabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanminabs + [@stdlib/stats/strided/scumax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/scumax [@stdlib/stats/strided/scumaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/scumaxabs @@ -411,8 +500,12 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/strided/smaxsorted]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/smaxsorted +[@stdlib/stats/strided/smean]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/smean + [@stdlib/stats/strided/smeanli]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/smeanli +[@stdlib/stats/strided/smeanpn]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/smeanpn + [@stdlib/stats/strided/smeanpw]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/smeanpw [@stdlib/stats/strided/smeanwd]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/smeanwd @@ -457,6 +550,8 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/strided/srange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/srange +[@stdlib/stats/strided/sstdev]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/sstdev + [@stdlib/stats/strided/sstdevch]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/sstdevch [@stdlib/stats/strided/sstdevpn]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/sstdevpn @@ -473,6 +568,10 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/strided/svarianceyc]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/svarianceyc +[@stdlib/stats/strided/sztest]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/sztest + +[@stdlib/stats/strided/ztest]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/ztest +