time-to-botec/squiggle/node_modules/@stdlib/stats/base/dstdevwd/lib/ndarray.js

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/**
* @license Apache-2.0
*
* Copyright (c) 2020 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
'use strict';
// MODULES //
var dvariancewd = require( './../../../base/dvariancewd' ).ndarray;
var sqrt = require( '@stdlib/math/base/special/sqrt' );
// MAIN //
/**
* Computes the standard deviation of a double-precision floating-point strided array using Welford's algorithm.
*
* ## References
*
* - Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 41920. doi:[10.1080/00401706.1962.10490022](https://doi.org/10.1080/00401706.1962.10490022).
* - van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 14950. doi:[10.1145/362929.362961](https://doi.org/10.1145/362929.362961).
*
* @param {PositiveInteger} N - number of indexed elements
* @param {number} correction - degrees of freedom adjustment
* @param {Float64Array} x - input array
* @param {integer} stride - stride length
* @param {NonNegativeInteger} offset - starting index
* @returns {number} standard deviation
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
* var floor = require( '@stdlib/math/base/special/floor' );
*
* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
* var N = floor( x.length / 2 );
*
* var v = dstdevwd( N, 1, x, 2, 1 );
* // returns 2.5
*/
function dstdevwd( N, correction, x, stride, offset ) {
return sqrt( dvariancewd( N, correction, x, stride, offset ) );
}
// EXPORTS //
module.exports = dstdevwd;