time-to-botec

Benchmark sampling in different programming languages
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factory.js (2098B)

      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 constantFunction = require( '@stdlib/utils/constant-function' );
     24 var isnan = require( '@stdlib/math/base/assert/is-nan' );
     25 var gamma = require( '@stdlib/math/base/special/gamma' );
     26 var EPS = require( '@stdlib/constants/float64/eps' );
     27 
     28 
     29 // MAIN //
     30 
     31 /**
     32 * Returns a function for evaluating the moment-generating function (MGF) of a Weibull distribution with shape `k` and scale `lambda`.
     33 *
     34 * @param {PositiveNumber} k - shape parameter
     35 * @param {PositiveNumber} lambda - scale parameter
     36 * @returns {Function} MGF
     37 *
     38 * @example
     39 * var mgf = factory( 8.0, 10.0 );
     40 *
     41 * var y = mgf( 0.8 );
     42 * // returns ~3150.149
     43 *
     44 * y = mgf( 0.08 );
     45 * // returns ~2.137
     46 */
     47 function factory( k, lambda ) {
     48 	if (
     49 		isnan( k ) ||
     50 		isnan( lambda ) ||
     51 		k <= 0.0 ||
     52 		lambda <= 0.0
     53 	) {
     54 		return constantFunction( NaN );
     55 	}
     56 	return mgf;
     57 
     58 	/**
     59 	* Evaluates the moment-generating function (MGF) for a Weibull distribution.
     60 	*
     61 	* @private
     62 	* @param {number} t - input value
     63 	* @returns {number} evaluated MGF
     64 	*
     65 	* @example
     66 	* var y = mgf( 0.5 );
     67 	* // returns <number>
     68 	*/
     69 	function mgf( t ) {
     70 		var summand;
     71 		var sum;
     72 		var c;
     73 		var n;
     74 
     75 		if ( isnan( t ) ) {
     76 			return NaN;
     77 		}
     78 		sum = 1.0;
     79 		c = 1.0;
     80 		n = 0;
     81 		do {
     82 			n += 1;
     83 			c *= ( t * lambda ) / n;
     84 			if ( c === 0.0 ) {
     85 				summand = 0.0;
     86 			} else {
     87 				summand = c * gamma( 1.0 + (n / k) );
     88 			}
     89 			sum += summand;
     90 		} while ( summand / sum > EPS );
     91 		return sum;
     92 	}
     93 }
     94 
     95 
     96 // EXPORTS //
     97 
     98 module.exports = factory;