factory.js (2068B)
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 kernelBetaincinv = require( '@stdlib/math/base/special/kernel-betaincinv' ); 25 var isnan = require( '@stdlib/math/base/assert/is-nan' ); 26 var sign = require( '@stdlib/math/base/special/signum' ); 27 var sqrt = require( '@stdlib/math/base/special/sqrt' ); 28 29 30 // MAIN // 31 32 /** 33 * Returns a function for evaluating the quantile function for a Student's t distribution with degrees of freedom `v`. 34 * 35 * @param {PositiveNumber} v - degrees of freedom 36 * @returns {Function} quantile function 37 * 38 * @example 39 * var quantile = factory( 0.5 ); 40 * var y = quantile( 0.5 ); 41 * // returns 0.0 42 * 43 * y = quantile( 0.8 ); 44 * // returns ~2.513 45 * 46 * y = quantile( 1.0 ); 47 * // returns Infinity 48 */ 49 function factory( v ) { 50 if ( isnan( v ) || v <= 0.0 ) { 51 return constantFunction( NaN ); 52 } 53 return quantile; 54 55 /** 56 * Evaluates the quantile function for a Student's t distribution. 57 * 58 * @private 59 * @param {Probability} p - input value 60 * @returns {number} evaluated quantile function 61 * 62 * @example 63 * var y = quantile( 0.3 ); 64 * // returns <number> 65 */ 66 function quantile( p ) { 67 var prob; 68 var xs; 69 70 if ( isnan( p ) || p < 0.0 || p > 1.0 ) { 71 return NaN; 72 } 73 prob = ( p > 0.5 ) ? 1.0 - p : p; 74 xs = kernelBetaincinv( v / 2.0, 0.5, 2.0 * prob, 1.0 - (2.0 * prob) ); 75 return sign( p - 0.5 ) * sqrt( v * xs[ 1 ] / xs[ 0 ] ); 76 } 77 } 78 79 80 // EXPORTS // 81 82 module.exports = factory;