time-to-botec

Benchmark sampling in different programming languages
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factory.js (1922B)


      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 beta = require( '@stdlib/math/base/special/beta' );
     26 var sqrt = require( '@stdlib/math/base/special/sqrt' );
     27 var pow = require( '@stdlib/math/base/special/pow' );
     28 
     29 
     30 // MAIN //
     31 
     32 /**
     33 * Returns a function for evaluating the probability density function (PDF) for a Student's t distribution with `v` degrees of freedom.
     34 *
     35 * @param {PositiveNumber} v - degrees of freedom
     36 * @returns {Function} PDF
     37 *
     38 * @example
     39 * var pdf = factory( 1.0 );
     40 * var y = pdf( 3.0 );
     41 * // returns ~0.032
     42 *
     43 * y = pdf( 1.0 );
     44 * // returns ~0.159
     45 */
     46 function factory( v ) {
     47 	var exponent;
     48 	var betaTerm;
     49 
     50 	if ( isnan( v ) || v <= 0 ) {
     51 		return constantFunction( NaN );
     52 	}
     53 	betaTerm = sqrt( v ) * beta( v/2.0, 0.5 );
     54 	exponent = ( 1.0 + v ) / 2.0;
     55 	return pdf;
     56 
     57 	/**
     58 	* Evaluates the probability density function (PDF) for a Student's t distribution.
     59 	*
     60 	* @private
     61 	* @param {number} x - input value
     62 	* @returns {number} evaluated PDF
     63 	*
     64 	* @example
     65 	* var y = pdf( 2.3 );
     66 	* // returns <number>
     67 	*/
     68 	function pdf( x ) {
     69 		if ( isnan( x ) ) {
     70 			return NaN;
     71 		}
     72 		return pow( v / ( v + pow( x, 2.0 ) ), exponent ) / betaTerm;
     73 	}
     74 }
     75 
     76 
     77 // EXPORTS //
     78 
     79 module.exports = factory;