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@stdlib/stats

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Standard library statistical functions.

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/** * @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 isNonNegativeInteger = require( '@stdlib/math/base/assert/is-nonnegative-integer' ); var constantFunction = require( '@stdlib/utils/constant-function' ); var binomcoefln = require( '@stdlib/math/base/special/binomcoefln' ); var degenerate = require( './../../../../../base/dists/degenerate/pmf' ).factory; var isnan = require( '@stdlib/math/base/assert/is-nan' ); var log1p = require( '@stdlib/math/base/special/log1p' ); var exp = require( '@stdlib/math/base/special/exp' ); var ln = require( '@stdlib/math/base/special/ln' ); var PINF = require( '@stdlib/constants/float64/pinf' ); // MAIN // /** * Returns a function for evaluating the probability mass function (PMF) for a binomial distribution with number of trials `n` and success probability `p`. * * @param {NonNegativeInteger} n - number of trials * @param {Probability} p - success probability * @returns {Function} PMF * * @example * var pmf = factory( 10, 0.5 ); * var y = pmf( 3.0 ); * // returns ~0.117 * * y = pmf( 5.0 ); * // returns ~0.246 */ function factory( n, p ) { if ( isnan( n ) || isnan( p ) || !isNonNegativeInteger( n ) || n === PINF || p < 0.0 || p > 1.0 ) { return constantFunction( NaN ); } if ( p === 0.0 || n === 0 ) { return degenerate( 0.0 ); } if ( p === 1.0 ) { return degenerate( n ); } return pmf; /** * Evaluates the probability mass function (PMF) for a binomial distribution. * * @private * @param {number} x - input value * @returns {Probability} evaluated PMF * * @example * var y = pmf( 2.0 ); * // returns <number> */ function pmf( x ) { var lnl; if ( isnan( x ) ) { return NaN; } if ( isNonNegativeInteger( x ) ) { if ( x > n ) { return 0.0; } lnl = binomcoefln( n, x ); lnl += (x * ln( p )) + ((n - x) * log1p( -p )); return exp( lnl ); } return 0.0; } } // EXPORTS // module.exports = factory;