mgf.js (2080B)
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 exp = require( '@stdlib/math/base/special/exp' ); 25 var pow = require( '@stdlib/math/base/special/pow' ); 26 var ln = require( '@stdlib/math/base/special/ln' ); 27 28 29 // MAIN // 30 31 /** 32 * Evaluates the moment-generating function (MGF) for a negative binomial distribution. 33 * 34 * @param {number} t - input value 35 * @param {PositiveNumber} r - number of successes until experiment is stopped 36 * @param {Probability} p - success probability 37 * @returns {number} evaluated MGF 38 * 39 * @example 40 * var y = mgf( 0.05, 20.0, 0.8 ); 41 * // returns ~267.839 42 * 43 * @example 44 * var y = mgf( 0.1, 20.0, 0.1 ); 45 * // returns ~9.347 46 * 47 * @example 48 * var y = mgf( 0.5, 10.0, 0.4 ); 49 * // returns ~42822.023 50 * 51 * @example 52 * var y = mgf( 0.1, 0.0, 0.5 ); 53 * // returns NaN 54 * 55 * @example 56 * var y = mgf( 0.1, -2.0, 0.5 ); 57 * // returns NaN 58 * 59 * @example 60 * var y = mgf( NaN, 20.0, 0.5 ); 61 * // returns NaN 62 * 63 * @example 64 * var y = mgf( 0.0, NaN, 0.5 ); 65 * // returns NaN 66 * 67 * @example 68 * var y = mgf( 0.0, 20.0, NaN ); 69 * // returns NaN 70 * 71 * @example 72 * var y = mgf( 0.2, 20, -1.0 ); 73 * // returns NaN 74 * 75 * @example 76 * var y = mgf( 0.2, 20, 1.5 ); 77 * // returns NaN 78 */ 79 function mgf( t, r, p ) { 80 if ( 81 isnan( t ) || 82 isnan( r ) || 83 isnan( p ) || 84 r <= 0.0 || 85 p < 0.0 || 86 p > 1.0 || 87 t >= -ln( p ) 88 ) { 89 return NaN; 90 } 91 return pow( ( (1.0 - p) * exp( t ) ) / ( 1.0 - (p * exp( t )) ), r ); 92 } 93 94 95 // EXPORTS // 96 97 module.exports = mgf;