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@stdlib/stats

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Standard library statistical functions.

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/** * @license Apache-2.0 * * Copyright (c) 2018 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 isnan = require( '@stdlib/math/base/assert/is-nan' ); var beta = require( '@stdlib/math/base/special/beta' ); // MAIN // /** * Returns the excess kurtosis of a Kumaraswamy's double bounded distribution. * * @param {PositiveNumber} a - first shape parameter * @param {PositiveNumber} b - second shape parameter * @returns {number} excess kurtosis * * @example * var v = kurtosis( 0.5, 1.0 ); * // returns ~2.143 * * @example * var v = kurtosis( 4.0, 12.0 ); * // returns ~2.704 * * @example * var v = kurtosis( 12.0, 2.0 ); * // returns ~4.817 * * @example * var v = kurtosis( 1.0, -0.1 ); * // returns NaN * * @example * var v = kurtosis( -0.1, 1.0 ); * // returns NaN * * @example * var v = kurtosis( 2.0, NaN ); * // returns NaN * * @example * var v = kurtosis( NaN, 2.0 ); * // returns NaN */ function kurtosis( a, b ) { var sigma2; var out; var mu2; var m1; var m2; var m3; var m4; if ( isnan( a ) || a <= 0.0 || isnan( b ) || b <= 0.0 ) { return NaN; } m1 = b * beta( 1.0 + ( 1.0/a ), b ); m2 = b * beta( 1.0 + ( 2.0/a ), b ); m3 = b * beta( 1.0 + ( 3.0/a ), b ); m4 = b * beta( 1.0 + ( 4.0/a ), b ); sigma2 = m2 - ( m1*m1 ); mu2 = m1 * m1; out = ( m4 - ( 4.0*m3*m1 ) + ( 6.0*m2*mu2 ) - ( 3.0*mu2*mu2 ) ); out /= sigma2*sigma2; return out; } // EXPORTS // module.exports = kurtosis;