time-to-botec

Benchmark sampling in different programming languages
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factory.js (1808B)


      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 mgf0 = require( './_mgf.js' );
     26 
     27 
     28 // MAIN //
     29 
     30 /**
     31 * Returns a function for evaluating the moment-generating function (MGF) for a beta distribution with first shape parameter `alpha` and second shape parameter `beta`.
     32 *
     33 * @param {PositiveNumber} alpha - first shape parameter
     34 * @param {PositiveNumber} beta - second shape parameter
     35 * @returns {Function} MGF
     36 *
     37 * @example
     38 * var mgf = factory( 0.5, 0.5 );
     39 *
     40 * var y = mgf( 0.8 );
     41 * // returns ~1.552
     42 *
     43 * y = mgf( 0.3 );
     44 * // returns ~1.168
     45 */
     46 function factory( alpha, beta ) {
     47 	if (
     48 		isnan( alpha ) ||
     49 		isnan( beta ) ||
     50 		alpha <= 0.0 ||
     51 		beta <= 0.0
     52 	) {
     53 		return constantFunction( NaN );
     54 	}
     55 	return mgf;
     56 
     57 	/**
     58 	* Evaluates the moment-generating function (MGF) for a beta distribution.
     59 	*
     60 	* @private
     61 	* @param {number} t - input value
     62 	* @returns {number} evaluated MGF
     63 	*
     64 	* @example
     65 	* var y = mgf( 2.0 );
     66 	* // returns <number>
     67 	*/
     68 	function mgf( t ) {
     69 		if ( isnan( t ) ) {
     70 			return NaN;
     71 		}
     72 		return mgf0( t, alpha, beta );
     73 	}
     74 }
     75 
     76 
     77 // EXPORTS //
     78 
     79 module.exports = factory;