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 | 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 3012x 3012x 3012x 3012x 3012x 3012x 3012x 3012x 3003x 3012x 12x 12x 3000x 3000x 3000x 3000x 3012x 2x 2x 2x 2x 2x | /** * @license Apache-2.0 * * Copyright (c) 2025 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 // /** * Evaluates the probability density function (PDF) for a Burr (type III) distribution with first shape parameter `alpha` and second shape parameter `beta` at a value `x`. * * @param {number} x - input value * @param {PositiveNumber} alpha - first shape parameter * @param {PositiveNumber} beta - second shape parameter * @returns {number} evaluated PDF * * @example * var v = pdf( 1, 1.0, 1.0 ); * // returns 0.25 * * @example * var v = pdf( 4, 4.0, 4.0 ); * // returns ~0.0153 * * @example * var v = pdf( 3, 3.0, 3.0 ); * // returns ~0.096 * * @example * var v = pdf( 1, NaN, 1.0 ); * // returns NaN * * @example * var v = pdf( 1, 1.0, NaN ); * // returns NaN */ function pdf( x, alpha, beta ) { var out; if ( isnan( x ) || isnan( alpha ) || isnan( beta ) || alpha <= 0.0 || beta <= 0.0 || x <= 0.0 ) { return NaN; } out = alpha * beta; out *= pow( x, -alpha-1 ); out /= pow( 1 + pow( x, -alpha ), beta + 1 ); return out; } // EXPORTS // module.exports = pdf; |