quantile.js (1973B)
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 var sign = require( '@stdlib/math/base/special/signum' ); 26 var sqrt = require( '@stdlib/math/base/special/sqrt' ); 27 28 29 // MAIN // 30 31 /** 32 * Evaluates the quantile function for a Student's t distribution with degrees of freedom `v` at a probability `p`. 33 * 34 * @param {Probability} p - input value 35 * @param {PositiveNumber} v - degrees of freedom 36 * @returns {number} evaluated quantile function 37 * 38 * @example 39 * var y = quantile( 0.8, 1.0 ); 40 * // returns ~1.376 41 * 42 * @example 43 * var y = quantile( 0.1, 1.0 ); 44 * // returns ~-3.078 45 * 46 * @example 47 * var y = quantile( 0.5, 0.1 ); 48 * // returns 0.0 49 * 50 * @example 51 * var y = quantile( -0.2, 0.1 ); 52 * // returns NaN 53 * 54 * @example 55 * var y = quantile( NaN, 1.0 ); 56 * // returns NaN 57 * 58 * @example 59 * var y = quantile( 0.0, NaN ); 60 * // returns NaN 61 * 62 * @example 63 * var y = quantile( 0.5, -1.0 ); 64 * // returns NaN 65 */ 66 function quantile( p, v ) { 67 var prob; 68 var xs; 69 if ( 70 isnan( v ) || 71 isnan( p ) || 72 v <= 0.0 || 73 p < 0.0 || 74 p > 1.0 75 ) { 76 return NaN; 77 } 78 prob = ( p > 0.5 ) ? 1.0 - p : p; 79 xs = kernelBetaincinv( v / 2.0, 0.5, 2.0 * prob, 1.0 - (2.0 * prob) ); 80 return sign( p - 0.5 ) * sqrt( v * xs[ 1 ] / xs[ 0 ] ); 81 } 82 83 84 // EXPORTS // 85 86 module.exports = quantile;