logpdf.js (2225B)
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 PINF = require( '@stdlib/constants/float64/pinf' ); 27 var NINF = require( '@stdlib/constants/float64/ninf' ); 28 29 30 // MAIN // 31 32 /** 33 * Evaluates the natural logarithm of the probability density function (PDF) for a Weibull distribution with shape parameter `k` and scale parameter `lambda` at a value `x`. 34 * 35 * @param {number} x - input value 36 * @param {PositiveNumber} k - shape parameter 37 * @param {PositiveNumber} lambda - scale parameter 38 * @returns {number} evaluated logarithm of probability density function 39 * 40 * @example 41 * var y = logpdf( 2.0, 1.0, 0.5 ); 42 * // returns ~-3.307 43 * 44 * @example 45 * var y = logpdf( 0.1, 1.0, 1.0 ); 46 * // returns ~-0.1 47 * 48 * @example 49 * var y = logpdf( -1.0, 4.0, 2.0 ); 50 * // returns -Infinity 51 * 52 * @example 53 * var y = logpdf( NaN, 0.6, 1.0 ); 54 * // returns NaN 55 * 56 * @example 57 * var y = logpdf( 0.0, NaN, 1.0 ); 58 * // returns NaN 59 * 60 * @example 61 * var y = logpdf( 0.0, 0.0, NaN ); 62 * // returns NaN 63 * 64 * @example 65 * var y = logpdf( 2.0, 0.0, -1.0 ); 66 * // returns NaN 67 */ 68 function logpdf( x, k, lambda ) { 69 var xol; 70 if ( 71 isnan( k ) || 72 isnan( lambda ) || 73 k <= 0.0 || 74 lambda <= 0.0 75 ) { 76 return NaN; 77 } 78 if ( x < 0.0 ) { 79 return NINF; 80 } 81 if ( x === PINF || x === NINF ) { 82 return NINF; 83 } 84 if ( x === 0.0 ) { 85 return ( k === 1.0 ) ? ln( k/lambda ): NINF; 86 } 87 xol = x / lambda; 88 return ln( k / lambda ) + ( ( k - 1.0 ) * ln( xol ) ) - pow( xol, k ); 89 } 90 91 92 // EXPORTS // 93 94 module.exports = logpdf;