quantile.js (2102B)
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 kernelBetaincinv = require( '@stdlib/math/base/special/kernel-betaincinv' ); 24 var isnan = require( '@stdlib/math/base/assert/is-nan' ); 25 26 27 // MAIN // 28 29 /** 30 * Evaluates the quantile function for an F distribution with numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at a probability `p`. 31 * 32 * @param {Probability} p - input value 33 * @param {PositiveNumber} d1 - numerator degrees of freedom 34 * @param {PositiveNumber} d2 - denominator degrees of freedom 35 * @returns {number} evaluated quantile function 36 * 37 * @example 38 * var y = quantile( 0.8, 1.0, 1.0 ); 39 * // returns ~9.472 40 * 41 * @example 42 * var y = quantile( 0.5, 4.0, 2.0 ); 43 * // returns ~1.207 44 * 45 * @example 46 * var y = quantile( 1.1, 1.0, 1.0 ); 47 * // returns NaN 48 * 49 * @example 50 * var y = quantile( -0.2, 1.0, 1.0 ); 51 * // returns NaN 52 * 53 * @example 54 * var y = quantile( NaN, 1.0, 1.0 ); 55 * // returns NaN 56 * 57 * @example 58 * var y = quantile( 0.5, NaN, 1.0 ); 59 * // returns NaN 60 * 61 * @example 62 * var y = quantile( 0.5, 1.0, NaN ); 63 * // returns NaN 64 * 65 * @example 66 * var y = quantile( 0.5, -1.0, 1.0 ); 67 * // returns NaN 68 * 69 * @example 70 * var y = quantile( 0.5, 1.0, -1.0 ); 71 * // returns NaN 72 */ 73 function quantile( p, d1, d2 ) { 74 var xs; 75 if ( 76 isnan( p ) || 77 isnan( d1 ) || 78 isnan( d2 ) || 79 d1 <= 0.0 || 80 d2 <= 0.0 || 81 p < 0.0 || 82 p > 1.0 83 ) { 84 return NaN; 85 } 86 xs = kernelBetaincinv( d1/2.0, d2/2.0, p, 1.0 - p ); 87 return d2 * xs[ 0 ] / ( d1 * xs[ 1 ] ); 88 } 89 90 91 // EXPORTS // 92 93 module.exports = quantile;