time-to-botec

Benchmark sampling in different programming languages
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factory.js (1917B)


      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 pow = require( '@stdlib/math/base/special/pow' );
     26 
     27 
     28 // MAIN //
     29 
     30 /**
     31 * Returns a function for evaluating the quantile function for a Kumaraswamy's double bounded distribution with first shape parameter `a` and second shape parameter `b`.
     32 *
     33 * @param {PositiveNumber} a - first shape parameter
     34 * @param {PositiveNumber} b - second shape parameter
     35 * @returns {Function} quantile function
     36 *
     37 * @example
     38 * var quantile = factory( 0.5, 0.5 );
     39 *
     40 * var y = quantile( 0.8 );
     41 * // returns ~0.922
     42 *
     43 * y = quantile( 0.3 );
     44 * // returns ~0.26
     45 */
     46 function factory( a, b ) {
     47 	if (
     48 		isnan( a ) ||
     49 		isnan( b ) ||
     50 		a <= 0.0 ||
     51 		b <= 0.0
     52 	) {
     53 		return constantFunction( NaN );
     54 	}
     55 	return quantile;
     56 
     57 	/**
     58 	* Evaluates the quantile function for a Kumaraswamy's double bounded distribution.
     59 	*
     60 	* @private
     61 	* @param {Probability} p - input probability
     62 	* @returns {number} evaluated quantile function
     63 	*
     64 	* @example
     65 	* var y = quantile( 2.0 );
     66 	* // returns <number>
     67 	*/
     68 	function quantile( p ) {
     69 		if ( isnan( p ) || p < 0.0 || p > 1.0 ) {
     70 			return NaN;
     71 		}
     72 		return pow( 1.0 - pow( 1.0-p, 1.0/b ), 1.0/a );
     73 	}
     74 }
     75 
     76 
     77 // EXPORTS //
     78 
     79 module.exports = factory;