time-to-botec

Benchmark sampling in different programming languages
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pmf.js (2387B)

      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 isNonNegativeInteger = require( '@stdlib/math/base/assert/is-nonnegative-integer' );
     25 var ibetaDerivative = require( './ibeta_derivative.js' );
     26 
     27 
     28 // MAIN //
     29 
     30 /**
     31 * Evaluates the probability mass function (PMF) for a negative binomial distribution with number of successes until experiment is stopped `r` and success probability `p`.
     32 *
     33 * @param {number} x - input value
     34 * @param {PositiveNumber} r - number of successes until experiment is stopped
     35 * @param {Probability} p - success probability
     36 * @returns {Probability} evaluated PMF
     37 *
     38 * @example
     39 * var y = pmf( 5.0, 20.0, 0.8 );
     40 * // returns ~0.157
     41 *
     42 * @example
     43 * var y = pmf( 21.0, 20.0, 0.5 );
     44 * // returns ~0.06
     45 *
     46 * @example
     47 * var y = pmf( 5.0, 10.0, 0.4 );
     48 * // returns ~0.016
     49 *
     50 * @example
     51 * var y = pmf( 0.0, 10.0, 0.9 );
     52 * // returns ~0.349
     53 *
     54 * @example
     55 * var y = pmf( 21.0, 15.5, 0.5 );
     56 * // returns ~0.037
     57 *
     58 * @example
     59 * var y = pmf( 5.0, 7.4, 0.4 );
     60 * // returns ~0.051
     61 *
     62 * @example
     63 * var y = pmf( 2.0, 0.0, 0.5 );
     64 * // returns NaN
     65 *
     66 * @example
     67 * var y = pmf( 2.0, -2.0, 0.5 );
     68 * // returns NaN
     69 *
     70 * @example
     71 * var y = pmf( 2.0, 20, -1.0 );
     72 * // returns NaN
     73 *
     74 * @example
     75 * var y = pmf( 2.0, 20, 1.5 );
     76 * // returns NaN
     77 *
     78 * @example
     79 * var y = pmf( NaN, 20.0, 0.5 );
     80 * // returns NaN
     81 *
     82 * @example
     83 * var y = pmf( 0.0, NaN, 0.5 );
     84 * // returns NaN
     85 *
     86 * @example
     87 * var y = pmf( 0.0, 20.0, NaN );
     88 * // returns NaN
     89 */
     90 function pmf( x, r, p ) {
     91 	if (
     92 		isnan( x ) ||
     93 		isnan( r ) ||
     94 		isnan( p ) ||
     95 		r <= 0.0 ||
     96 		p <= 0.0 ||
     97 		p > 1.0
     98 	) {
     99 		return NaN;
    100 	}
    101 	if ( !isNonNegativeInteger( x ) || p === 0.0 ) {
    102 		return 0.0;
    103 	}
    104 	return ( p / ( r + x ) ) * ibetaDerivative( p, r, x + 1.0 );
    105 }
    106 
    107 
    108 // EXPORTS //
    109 
    110 module.exports = pmf;