time-to-botec

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

factory.js (2962B)

      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 isNonNegativeInteger = require( '@stdlib/math/base/assert/is-nonnegative-integer' );
     24 var isnan = require( '@stdlib/math/base/assert/is-nan' );
     25 var constantFunction = require( '@stdlib/utils/constant-function' );
     26 var trunc = require( '@stdlib/math/base/special/trunc' );
     27 var max = require( '@stdlib/math/base/special/max' );
     28 var min = require( '@stdlib/math/base/special/min' );
     29 var pmf = require( './../../../../../base/dists/hypergeometric/pmf' );
     30 var PINF = require( '@stdlib/constants/float64/pinf' );
     31 var Float64Array = require( '@stdlib/array/float64' );
     32 var sum = require( './sum.js' );
     33 
     34 
     35 // MAIN //
     36 
     37 /**
     38 * Returns a function for evaluating the cumulative distribution function (CDF) for a hypergeometric distribution with population size `N`, subpopulation size `K`, and number of draws `n`.
     39 *
     40 * @param {NonNegativeInteger} N - population size
     41 * @param {NonNegativeInteger} K - subpopulation size
     42 * @param {NonNegativeInteger} n - number of draws
     43 * @returns {Function} CDF
     44 *
     45 * @example
     46 * var mycdf = factory( 30, 20, 5 );
     47 * var y = mycdf( 4.0 );
     48 * // returns ~0.891
     49 *
     50 * y = mycdf( 1.0 );
     51 * // returns ~0.031
     52 */
     53 function factory( N, K, n ) {
     54 	if (
     55 		isnan( N ) ||
     56 		isnan( K ) ||
     57 		isnan( n ) ||
     58 		!isNonNegativeInteger( N ) ||
     59 		!isNonNegativeInteger( K ) ||
     60 		!isNonNegativeInteger( n ) ||
     61 		N === PINF ||
     62 		K === PINF ||
     63 		K > N ||
     64 		n > N
     65 	) {
     66 		return constantFunction( NaN );
     67 	}
     68 	return cdf;
     69 
     70 	/**
     71 	* Evaluates the cumulative distribution function (CDF) for a hypergeometric distribution.
     72 	*
     73 	* @private
     74 	* @param {number} x - input value
     75 	* @returns {Probability} evaluated CDF
     76 	*
     77 	* @example
     78 	* var y = cdf( 2.0 );
     79 	* // returns <number>
     80 	*/
     81 	function cdf( x ) {
     82 		var denom;
     83 		var probs;
     84 		var num;
     85 		var ret;
     86 		var i;
     87 
     88 		if ( isnan( x ) ) {
     89 			return NaN;
     90 		}
     91 		x = trunc( x );
     92 		if ( x < max( 0, n + K - N ) ) {
     93 			return 0.0;
     94 		}
     95 		if ( x >= min( n, K ) ) {
     96 			return 1.0;
     97 		}
     98 
     99 		probs = new Float64Array( x+1 );
    100 		probs[ x ] = pmf( x, N, K, n );
    101 
    102 		/*
    103 		* Use recurrence relation:
    104 		*
    105 		*   (x+1)( N - K - (n-x-1) )P(X=x+1)=(K-x)(n-x)P(X=x)
    106 		*/
    107 		for ( i = x-1; i >= 0; i-- ) {
    108 			num = ( i+1 ) * ( N-K-(n-i-1) );
    109 			denom = ( K-i ) * ( n-i );
    110 			probs[ i ] = ( num/denom ) * probs[ i+1 ];
    111 		}
    112 		ret = sum( probs );
    113 		return min( ret, 1.0 );
    114 	}
    115 }
    116 
    117 
    118 // EXPORTS //
    119 
    120 module.exports = factory;