logpdf.js (2352B)
1 /** 2 * @license Apache-2.0 3 * 4 * Copyright (c) 2018 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 isnan = require( '@stdlib/math/base/assert/is-nan' ); 24 var pow = require( '@stdlib/math/base/special/pow' ); 25 var ln = require( '@stdlib/math/base/special/ln' ); 26 var NINF = require( '@stdlib/constants/float64/ninf' ); 27 28 29 // MAIN // 30 31 /** 32 * Evaluates the natural logarithm of the probability density function (PDF) for a Kumaraswamy's double bounded distribution with first shape parameter `a` and second shape parameter `b` at a value `x`. 33 * 34 * @param {number} x - input value 35 * @param {PositiveNumber} a - first shape parameter 36 * @param {PositiveNumber} b - second shape parameter 37 * @returns {number} evaluated logPDF 38 * 39 * @example 40 * var y = logpdf( 0.5, 1.0, 1.0 ); 41 * // returns 0.0 42 * 43 * @example 44 * var y = logpdf( 0.5, 2.0, 4.0 ); 45 * // returns ~0.523 46 * 47 * @example 48 * var y = logpdf( 0.2, 2.0, 2.0 ); 49 * // returns ~-0.264 50 * 51 * @example 52 * var y = logpdf( 0.8, 4.0, 4.0 ); 53 * // returns ~0.522 54 * 55 * @example 56 * var y = logpdf( -0.5, 4.0, 2.0 ); 57 * // returns -Infinity 58 * 59 * @example 60 * var y = logpdf( 1.5, 4.0, 2.0 ); 61 * // returns -Infinity 62 * 63 * @example 64 * var y = logpdf( 2.0, -1.0, 0.5 ); 65 * // returns NaN 66 * 67 * @example 68 * var y = logpdf( 2.0, 0.5, -1.0 ); 69 * // returns NaN 70 * 71 * @example 72 * var y = logpdf( NaN, 1.0, 1.0 ); 73 * // returns NaN 74 * 75 * @example 76 * var y = logpdf( 0.0, NaN, 1.0 ); 77 * // returns NaN 78 * 79 * @example 80 * var y = logpdf( 0.0, 1.0, NaN ); 81 * // returns NaN 82 */ 83 function logpdf( x, a, b ) { 84 var out; 85 86 if ( 87 isnan( x ) || 88 isnan( a ) || 89 isnan( b ) || 90 a <= 0.0 || 91 b <= 0.0 92 ) { 93 return NaN; 94 } 95 if ( x <= 0.0 || x >= 1.0 ) { 96 return NINF; 97 } 98 out = ln( a*b ); 99 out += ( a - 1.0 ) * ln( x ); 100 out += ( b - 1.0 ) * ln( 1.0 - pow( x, a ) ); 101 return out; 102 } 103 104 105 // EXPORTS // 106 107 module.exports = logpdf;