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* Computes the standard deviation of a one-dimensional double-precision floating-point ndarray using a one-pass textbook algorithm.
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*
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* @param arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying a degrees of freedom adjustment
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* @returns standard deviation
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*
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* @example
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* var ndarray = require( '@stdlib/ndarray/ctor' );
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* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
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* var Float64Array = require( '@stdlib/array/float64' );
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*
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* var opts = {
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* 'dtype': 'float64'
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* };
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*
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* var xbuf = new Float64Array( [ 1.0, -2.0, 2.0 ] );
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* var x = new ndarray( opts.dtype, xbuf, [ 3 ], [ 1 ], 0, 'row-major' );
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* var correction = scalar2ndarray( 1.0, opts );
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*
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* var v = ns.dstdevtk( [ x, correction ] );
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* // returns ~2.0817
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*/
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dstdevtk: typeofdstdevtk;
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/**
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* Computes the standard deviation of a one-dimensional double-precision floating-point ndarray using Welford's algorithm.
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*
@@ -1241,6 +1269,30 @@ interface Namespace {
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*/
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dstdevwd: typeofdstdevwd;
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/**
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* Computes the standard deviation of a one-dimensional double-precision floating-point ndarray using a one-pass algorithm proposed by Youngs and Cramer.
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*
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* @param arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying a degrees of freedom adjustment
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* @returns standard deviation
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*
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* @example
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* var ndarray = require( '@stdlib/ndarray/ctor' );
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* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
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* var Float64Array = require( '@stdlib/array/float64' );
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*
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* var opts = {
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* 'dtype': 'float64'
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* };
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*
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* var xbuf = new Float64Array( [ 1.0, -2.0, 2.0 ] );
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* var x = new ndarray( opts.dtype, xbuf, [ 3 ], [ 1 ], 0, 'row-major' );
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* var correction = scalar2ndarray( 1.0, opts );
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*
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* var v = ns.dstdevyc( [ x, correction ] );
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* // returns ~2.0817
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*/
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dstdevyc: typeofdstdevyc;
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/**
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* Computes a one-sample Z-test for a one-dimensional double-precision floating-point ndarray.
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*
@@ -3162,6 +3214,30 @@ interface Namespace {
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*/
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sstdevpn: typeofsstdevpn;
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/**
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* Computes the standard deviation of a one-dimensional single-precision floating-point ndarray using a one-pass textbook algorithm.
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*
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* @param arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying a degrees of freedom adjustment
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* @returns standard deviation
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*
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* @example
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* var ndarray = require( '@stdlib/ndarray/ctor' );
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* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
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* var Float32Array = require( '@stdlib/array/float32' );
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*
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* var opts = {
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* 'dtype': 'float32'
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* };
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*
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* var xbuf = new Float32Array( [ 1.0, -2.0, 2.0 ] );
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* var x = new ndarray( opts.dtype, xbuf, [ 3 ], [ 1 ], 0, 'row-major' );
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* var correction = scalar2ndarray( 1.0, opts );
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*
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* var v = ns.sstdevtk( [ x, correction ] );
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* // returns ~2.0817
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*/
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sstdevtk: typeofsstdevtk;
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/**
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* Computes the standard deviation of a one-dimensional single-precision floating-point ndarray using Welford's algorithm.
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*
@@ -3186,6 +3262,30 @@ interface Namespace {
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*/
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sstdevwd: typeofsstdevwd;
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/**
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* Computes the standard deviation of a one-dimensional single-precision floating-point ndarray using a one-pass algorithm proposed by Youngs and Cramer.
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*
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* @param arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying a degrees of freedom adjustment
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* @returns standard deviation
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*
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* @example
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* var ndarray = require( '@stdlib/ndarray/ctor' );
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* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
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* var Float32Array = require( '@stdlib/array/float32' );
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*
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* var opts = {
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* 'dtype': 'float32'
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* };
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*
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* var xbuf = new Float32Array( [ 1.0, -2.0, 2.0 ] );
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* var x = new ndarray( opts.dtype, xbuf, [ 3 ], [ 1 ], 0, 'row-major' );
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* var correction = scalar2ndarray( 1.0, opts );
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*
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* var v = ns.sstdevyc( [ x, correction ] );
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* // returns ~2.0817
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*/
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sstdevyc: typeofsstdevyc;
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/**
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* Computes the standard deviation of a one-dimensional ndarray.
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