56 lines
1.6 KiB
JavaScript
56 lines
1.6 KiB
JavaScript
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/**
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* @license Apache-2.0
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*
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* Copyright (c) 2020 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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// MODULES //
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var varianceyc = require( './../../../base/varianceyc' );
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var sqrt = require( '@stdlib/math/base/special/sqrt' );
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// MAIN //
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/**
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* Computes the standard deviation of a strided array using a one-pass algorithm proposed by Youngs and Cramer.
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*
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* ## References
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*
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* - Youngs, Edward A., and Elliot M. Cramer. 1971. "Some Results Relevant to Choice of Sum and Sum-of-Product Algorithms." _Technometrics_ 13 (3): 657–65. doi:[10.1080/00401706.1971.10488826](https://doi.org/10.1080/00401706.1971.10488826).
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*
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* @param {PositiveInteger} N - number of indexed elements
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* @param {number} correction - degrees of freedom adjustment
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* @param {NumericArray} x - input array
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* @param {integer} stride - stride length
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* @returns {number} standard deviation
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*
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* @example
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* var x = [ 1.0, -2.0, 2.0 ];
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*
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* var v = stdevyc( x.length, 1, x, 1 );
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* // returns ~2.0817
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*/
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function stdevyc( N, correction, x, stride ) {
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return sqrt( varianceyc( N, correction, x, stride ) );
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}
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// EXPORTS //
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module.exports = stdevyc;
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