ndarray.js (2011B)
1 /** 2 * @license Apache-2.0 3 * 4 * Copyright (c) 2020 The Stdlib Authors. 5 * 6 * Licensed under the Apache License, Version 2.0 (the "License"); 7 * you may not use this file except in compliance with the License. 8 * You may obtain a copy of the License at 9 * 10 * http://www.apache.org/licenses/LICENSE-2.0 11 * 12 * Unless required by applicable law or agreed to in writing, software 13 * distributed under the License is distributed on an "AS IS" BASIS, 14 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 15 * See the License for the specific language governing permissions and 16 * limitations under the License. 17 */ 18 19 'use strict'; 20 21 // MODULES // 22 23 var variancewd = require( './../../../base/variancewd' ).ndarray; 24 var sqrt = require( '@stdlib/math/base/special/sqrt' ); 25 26 27 // MAIN // 28 29 /** 30 * Computes the standard deviation of a strided array using Welford's algorithm. 31 * 32 * ## References 33 * 34 * - Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022](https://doi.org/10.1080/00401706.1962.10490022). 35 * - van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961](https://doi.org/10.1145/362929.362961). 36 * 37 * @param {PositiveInteger} N - number of indexed elements 38 * @param {number} correction - degrees of freedom adjustment 39 * @param {NumericArray} x - input array 40 * @param {integer} stride - stride length 41 * @param {NonNegativeInteger} offset - starting index 42 * @returns {number} standard deviation 43 * 44 * @example 45 * var floor = require( '@stdlib/math/base/special/floor' ); 46 * 47 * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; 48 * var N = floor( x.length / 2 ); 49 * 50 * var v = stdevwd( N, 1, x, 2, 1 ); 51 * // returns 2.5 52 */ 53 function stdevwd( N, correction, x, stride, offset ) { 54 return sqrt( variancewd( N, correction, x, stride, offset ) ); 55 } 56 57 58 // EXPORTS // 59 60 module.exports = stdevwd;