time-to-botec

Benchmark sampling in different programming languages
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logpmf.js (2581B)

      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 ln = require( '@stdlib/math/base/special/ln' );
     26 var NINF = require( '@stdlib/constants/float64/ninf' );
     27 var ibetaDerivative = require( './ibeta_derivative.js' );
     28 
     29 
     30 // MAIN //
     31 
     32 /**
     33 * Evaluates the natural logarithm of the probability mass function (PMF) for a negative binomial distribution with number of successes until experiment is stopped `r` and success probability `p`.
     34 *
     35 * @param {number} x - input value
     36 * @param {PositiveNumber} r - number of successes until experiment is stopped
     37 * @param {Probability} p - success probability
     38 * @returns {number} evaluated logPMF
     39 *
     40 * @example
     41 * var y = logpmf( 5.0, 20.0, 0.8 );
     42 * // returns ~-1.853
     43 *
     44 * @example
     45 * var y = logpmf( 21.0, 20.0, 0.5 );
     46 * // returns ~-2.818
     47 *
     48 * @example
     49 * var y = logpmf( 5.0, 10.0, 0.4 );
     50 * // returns ~-4.115
     51 *
     52 * @example
     53 * var y = logpmf( 0.0, 10.0, 0.9 );
     54 * // returns ~-1.054
     55 *
     56 * @example
     57 * var y = logpmf( 21.0, 15.5, 0.5 );
     58 * // returns ~-3.292
     59 *
     60 * @example
     61 * var y = logpmf( 5.0, 7.4, 0.4 );
     62 * // returns ~-2.976
     63 *
     64 * @example
     65 * var y = logpmf( 2.0, 0.0, 0.5 );
     66 * // returns NaN
     67 *
     68 * @example
     69 * var y = logpmf( 2.0, -2.0, 0.5 );
     70 * // returns NaN
     71 *
     72 * @example
     73 * var y = logpmf( 2.0, 20, -1.0 );
     74 * // returns NaN
     75 *
     76 * @example
     77 * var y = logpmf( 2.0, 20, 1.5 );
     78 * // returns NaN
     79 *
     80 * @example
     81 * var y = logpmf( NaN, 20.0, 0.5 );
     82 * // returns NaN
     83 *
     84 * @example
     85 * var y = logpmf( 0.0, NaN, 0.5 );
     86 * // returns NaN
     87 *
     88 * @example
     89 * var y = logpmf( 0.0, 20.0, NaN );
     90 * // returns NaN
     91 */
     92 function logpmf( x, r, p ) {
     93 	if (
     94 		isnan( x ) ||
     95 		isnan( r ) ||
     96 		isnan( p ) ||
     97 		r <= 0.0 ||
     98 		p <= 0.0 ||
     99 		p > 1.0
    100 	) {
    101 		return NaN;
    102 	}
    103 	if ( !isNonNegativeInteger( x ) || p === 0.0 ) {
    104 		return NINF;
    105 	}
    106 	return ln( p ) - ln( r + x ) + ln( ibetaDerivative( p, r, x + 1.0 ) );
    107 }
    108 
    109 
    110 // EXPORTS //
    111 
    112 module.exports = logpmf;