Press n or j to go to the next uncovered block, b, p or k for the previous block.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 | 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1015x 1015x 1015x 1015x 1015x 1015x 1001x 1015x 15x 15x 1000x 1000x 1000x 1015x 1x 1x 1x 1x 1x | /** * @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 pow = require( '@stdlib/math/base/special/pow' ); // MAIN // /** * Returns the excess kurtosis of a Pareto (Type I) distribution. * * @param {PositiveNumber} alpha - shape parameter * @param {PositiveNumber} beta - scale parameter * @returns {PositiveNumber} excess kurtosis * * @example * var v = kurtosis( 5.0, 1.0 ); * // returns ~70.8 * * @example * var v = kurtosis( 7.0, 12.0 ); * // returns ~24.857 * * @example * var v = kurtosis( 8.0, 2.0 ); * // returns ~19.725 * * @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( alpha, beta ) { var out; if ( isnan( alpha ) || alpha <= 4.0 || isnan( beta ) || beta <= 0.0 ) { return NaN; } out = 6.0 * ( pow( alpha, 3.0 ) + pow( alpha, 2.0 ) - ( 6.0*alpha ) - 2.0 ); out /= alpha * ( alpha-3.0 ) * ( alpha-4.0 ); return out; } // EXPORTS // module.exports = kurtosis; |