pdf.js (2207B)
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 abs = require( '@stdlib/math/base/special/abs' ); 25 var exp = require( '@stdlib/math/base/special/exp' ); 26 var pow = require( '@stdlib/math/base/special/pow' ); 27 var NINF = require( '@stdlib/constants/float64/ninf' ); 28 var PINF = require( '@stdlib/constants/float64/pinf' ); 29 30 31 // MAIN // 32 33 /** 34 * Evaluates the probability density function (PDF) for a logistic distribution with location parameter `mu` and scale parameter `s` at a value `x`. 35 * 36 * @param {number} x - input value 37 * @param {number} mu - location parameter 38 * @param {NonNegativeNumber} s - scale parameter 39 * @returns {number} evaluated PDF 40 * 41 * @example 42 * var y = pdf( 2.0, 0.0, 1.0 ); 43 * // returns ~0.105 44 * 45 * @example 46 * var y = pdf( -1.0, 4.0, 2.0 ); 47 * // returns ~0.035 48 * 49 * @example 50 * var y = pdf( NaN, 0.0, 1.0 ); 51 * // returns NaN 52 * 53 * @example 54 * var y = pdf( 0.0, NaN, 1.0 ); 55 * // returns NaN 56 * 57 * @example 58 * var y = pdf( 0.0, 0.0, NaN ); 59 * // returns NaN 60 * 61 * @example 62 * // Negative scale parameter: 63 * var y = pdf( 2.0, 0.0, -1.0 ); 64 * // returns NaN 65 * 66 * @example 67 * var y = pdf( 2.0, 8.0, 0.0 ); 68 * // returns 0.0 69 * 70 * @example 71 * var y = pdf( 8.0, 8.0, 0.0 ); 72 * // returns Infinity 73 */ 74 function pdf( x, mu, s ) { 75 var ez; 76 var z; 77 if ( 78 isnan( x ) || 79 isnan( mu ) || 80 isnan( s ) || 81 s < 0.0 82 ) { 83 return NaN; 84 } 85 if ( x === NINF ) { 86 return 0.0; 87 } 88 if ( s === 0.0 ) { 89 return ( x === mu ) ? PINF : 0.0; 90 } 91 z = abs( ( x - mu ) / s ); 92 ez = exp( -z ); 93 return ez / ( s * pow( 1.0 + ez, 2.0 ) ); 94 } 95 96 97 // EXPORTS // 98 99 module.exports = pdf;