time-to-botec

Benchmark sampling in different programming languages
Log | Files | Refs | README

logpdf.js (2229B)

      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 NINF = require( '@stdlib/constants/float64/ninf' );
     27 var PI = require( '@stdlib/constants/float64/pi' );
     28 
     29 
     30 // MAIN //
     31 
     32 /**
     33 * Evaluates the natural logarithm of the probability density function (PDF) for a lognormal distribution with location parameter `mu` and scale parameter `sigma` at a value `x`.
     34 *
     35 * @param {number} x - input value
     36 * @param {number} mu - location parameter
     37 * @param {PositiveNumber} sigma - scale parameter
     38 * @returns {number} evaluated logPDF
     39 *
     40 * @example
     41 * var y = logpdf( 2.0, 0.0, 1.0 );
     42 * // returns ~-1.852
     43 *
     44 * @example
     45 * var y = logpdf( 1.0, 0.0, 1.0 );
     46 * // returns ~-0.919
     47 *
     48 * @example
     49 * var y = logpdf( 1.0, 3.0, 1.0 );
     50 * // returns ~-5.419
     51 *
     52 * @example
     53 * var y = logpdf( -1.0, 4.0, 2.0 );
     54 * // returns -Infinity
     55 *
     56 * @example
     57 * var y = logpdf( NaN, 0.0, 1.0 );
     58 * // returns NaN
     59 *
     60 * @example
     61 * var y = logpdf( 0.0, NaN, 1.0 );
     62 * // returns NaN
     63 *
     64 * @example
     65 * var y = logpdf( 0.0, 0.0, NaN );
     66 * // returns NaN
     67 *
     68 * @example
     69 * // Negative scale parameter:
     70 * var y = logpdf( 2.0, 0.0, -1.0 );
     71 * // returns NaN
     72 */
     73 function logpdf( x, mu, sigma ) {
     74 	var s2;
     75 	var A;
     76 	var B;
     77 	if (
     78 		isnan( x ) ||
     79 		isnan( mu ) ||
     80 		isnan( sigma ) ||
     81 		sigma <= 0.0
     82 	) {
     83 		return NaN;
     84 	}
     85 	if ( x <= 0.0 ) {
     86 		return NINF;
     87 	}
     88 	s2 = pow( sigma, 2.0 );
     89 	A = -0.5 * ln( 2.0 * s2 * PI );
     90 	B = -1.0 / ( 2.0 * s2 );
     91 	return A - ln( x ) + ( B * pow( ln(x) - mu, 2.0 ) );
     92 }
     93 
     94 
     95 // EXPORTS //
     96 
     97 module.exports = logpdf;