diff --git a/lib/node_modules/@stdlib/math/base/special/README.md b/lib/node_modules/@stdlib/math/base/special/README.md index 7c4896a63cb7..bb446bff5f3a 100644 --- a/lib/node_modules/@stdlib/math/base/special/README.md +++ b/lib/node_modules/@stdlib/math/base/special/README.md @@ -154,7 +154,7 @@ var fcns = special; - [`cabs2f( z )`][@stdlib/math/base/special/cabs2f]: compute the squared absolute value of a single-precision complex floating-point number. - [`cabsf( z )`][@stdlib/math/base/special/cabsf]: compute the absolute value of a single-precision complex floating-point number. - [`cceil( z )`][@stdlib/math/base/special/cceil]: round each component of a double-precision complex floating-point number toward positive infinity. -- [`cceilf( z )`][@stdlib/math/base/special/cceilf]: round a single-precision complex floating-point number toward positive infinity. +- [`cceilf( z )`][@stdlib/math/base/special/cceilf]: round each component of a single-precision complex floating-point number toward positive infinity. - [`cceiln( z, n )`][@stdlib/math/base/special/cceiln]: round each component of a double-precision complex floating-point number to the nearest multiple of `10^n` toward positive infinity. - [`ceil( x )`][@stdlib/math/base/special/ceil]: round a double-precision floating-point number toward positive infinity. - [`ceil10( x )`][@stdlib/math/base/special/ceil10]: round a numeric value to the nearest power of 10 toward positive infinity. diff --git a/lib/node_modules/@stdlib/stats/base/README.md b/lib/node_modules/@stdlib/stats/base/README.md index 19a3f44a3b3c..4034a6d79340 100644 --- a/lib/node_modules/@stdlib/stats/base/README.md +++ b/lib/node_modules/@stdlib/stats/base/README.md @@ -61,7 +61,7 @@ The namespace contains the following statistical functions: - [`cumaxabs( N, x, strideX, y, strideY )`][@stdlib/stats/base/cumaxabs]: calculate the cumulative maximum absolute value of a strided array. - [`cumin( N, x, strideX, y, strideY )`][@stdlib/stats/base/cumin]: calculate the cumulative minimum of a strided array. - [`cuminabs( N, x, strideX, y, strideY )`][@stdlib/stats/base/cuminabs]: calculate the cumulative minimum absolute value of a strided array. -- [`dmean( N, x, stride )`][@stdlib/stats/base/dmean]: calculate the arithmetic mean of a double-precision floating-point strided array. +- [`dmean( N, x, strideX )`][@stdlib/stats/base/dmean]: calculate the arithmetic mean of a double-precision floating-point strided array. - [`dmeanpn( N, x, strideX )`][@stdlib/stats/base/dmeanpn]: calculate the arithmetic mean of a double-precision floating-point strided array using a two-pass error correction algorithm. - [`dmeanstdev( N, correction, x, strideX, out, strideOut )`][@stdlib/stats/base/dmeanstdev]: calculate the mean and standard deviation of a double-precision floating-point strided array. - [`dmeanstdevpn( N, correction, x, strideX, out, strideOut )`][@stdlib/stats/base/dmeanstdevpn]: calculate the mean and standard deviation of a double-precision floating-point strided array using a two-pass algorithm. @@ -122,6 +122,7 @@ The namespace contains the following statistical functions: - [`nanvariancetk( N, correction, x, stride )`][@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. +- [`ndarray`][@stdlib/stats/base/ndarray]: base ndarray statistical functions. - [`rangeBy( N, x, stride, clbk[, thisArg] )`][@stdlib/stats/base/range-by]: calculate the range of a strided array via a callback function. - [`range( N, x, stride )`][@stdlib/stats/base/range]: calculate the range of a strided array. - [`sdsnanmean( N, x, stride )`][@stdlib/stats/base/sdsnanmean]: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using extended accumulation. @@ -131,7 +132,7 @@ The namespace contains the following statistical functions: - [`smeankbn2( N, x, stride )`][@stdlib/stats/base/smeankbn2]: calculate the arithmetic mean of a single-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm. - [`smeanlipw( N, x, stride )`][@stdlib/stats/base/smeanlipw]: calculate the arithmetic mean of a single-precision floating-point strided array using a one-pass trial mean algorithm with pairwise summation. - [`smeanors( N, x, stride )`][@stdlib/stats/base/smeanors]: calculate the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation. -- [`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. +- [`smeanpn( N, x, strideX )`][@stdlib/stats/base/smeanpn]: calculate the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm. - [`snanmean( N, x, stride )`][@stdlib/stats/base/snanmean]: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values. - [`snanmskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/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/base/snanmskmin]: calculate the minimum value of a single-precision floating-point strided array according to a mask, ignoring `NaN` values. @@ -344,6 +345,8 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/base/nanvarianceyc]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/nanvarianceyc +[@stdlib/stats/base/ndarray]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray + [@stdlib/stats/base/range-by]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/range-by [@stdlib/stats/base/range]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/range diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/README.md index b70f4c77c18a..1e16bbc857a5 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/README.md +++ b/lib/node_modules/@stdlib/stats/base/ndarray/README.md @@ -43,6 +43,14 @@ The namespace exposes the following APIs: +
+ +- [`dmax( arrays )`][@stdlib/stats/base/ndarray/dmax]: compute the maximum value of a one-dimensional double-precision floating-point ndarray. +- [`max( arrays )`][@stdlib/stats/base/ndarray/max]: compute the maximum value of a one-dimensional ndarray. +- [`smax( arrays )`][@stdlib/stats/base/ndarray/smax]: compute the maximum value of a one-dimensional single-precision floating-point ndarray. + +
+ @@ -80,6 +88,16 @@ 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/max]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/max + +[@stdlib/stats/base/ndarray/smax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/smax + + +