UNPKG

@stdlib/stats

Version:

Standard library statistical functions.

96 lines (86 loc) 2.09 kB
/** * @license Apache-2.0 * * Copyright (c) 2018 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ 'use strict'; // MODULES // var isnan = require( '@stdlib/math/base/assert/is-nan' ); var PINF = require( '@stdlib/constants/float64/pinf' ); var gammaDeriv = require( './gamma_p_derivative.js' ); // MAIN // /** * Evaluates the probability density function (PDF) for a gamma distribution with shape parameter `alpha` and rate parameter `beta` at a value `x`. * * @param {number} x - input value * @param {NonNegativeNumber} alpha - shape parameter * @param {PositiveNumber} beta - rate parameter * @returns {number} evaluated PDF * * @example * var y = pdf( 2.0, 0.5, 1.0 ); * // returns ~0.054 * * @example * var y = pdf( 0.1, 1.0, 1.0 ); * // returns ~0.905 * * @example * var y = pdf( -1.0, 4.0, 2.0 ); * // returns 0.0 * * @example * var y = pdf( NaN, 0.6, 1.0 ); * // returns NaN * * @example * var y = pdf( 0.0, NaN, 1.0 ); * // returns NaN * * @example * var y = pdf( 0.0, 1.0, NaN ); * // returns NaN * * @example * // Negative shape parameter: * var y = pdf( 2.0, -1.0, 1.0 ); * // returns NaN * * @example * // Negative rate parameter: * var y = pdf( 2.0, 1.0, -1.0 ); * // returns NaN */ function pdf( x, alpha, beta ) { if ( isnan( x ) || isnan( alpha ) || isnan( beta ) || alpha < 0.0 || beta <= 0.0 ) { return NaN; } if ( x < 0.0 || x === PINF ) { return 0.0; } if ( alpha === 0.0 ) { // Point mass at 0... return ( x === 0.0 ) ? PINF : 0.0; } return gammaDeriv( alpha, x * beta ) * beta; } // EXPORTS // module.exports = pdf;