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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. */ /* eslint-disable no-restricted-syntax, no-invalid-this */ 'use strict'; // MODULES // var isProbability = require( '@stdlib/assert/is-probability' ).isPrimitive; var defineProperty = require( '@stdlib/utils/define-property' ); var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); var setReadOnlyAccessor = require( '@stdlib/utils/define-nonenumerable-read-only-accessor' ); var isPositive = require( '@stdlib/assert/is-positive-number' ).isPrimitive; var kurtosis = require( './../../../../../base/dists/negative-binomial/kurtosis' ); var mean = require( './../../../../../base/dists/negative-binomial/mean' ); var mode = require( './../../../../../base/dists/negative-binomial/mode' ); var skewness = require( './../../../../../base/dists/negative-binomial/skewness' ); var stdev = require( './../../../../../base/dists/negative-binomial/stdev' ); var variance = require( './../../../../../base/dists/negative-binomial/variance' ); var cdf = require( './../../../../../base/dists/negative-binomial/cdf' ); var logpmf = require( './../../../../../base/dists/negative-binomial/logpmf' ); var mgf = require( './../../../../../base/dists/negative-binomial/mgf' ); var pmf = require( './../../../../../base/dists/negative-binomial/pmf' ); var quantile = require( './../../../../../base/dists/negative-binomial/quantile' ); var format = require( '@stdlib/string/format' ); // FUNCTIONS // /** * Evaluates the cumulative distribution function (CDF). * * @private * @param {number} x - input value * @returns {number} evaluated CDF */ function negativeBinomialCDF( x ) { return cdf( x, this.r, this.p ); } /** * Evaluates the natural logarithm of the probability mass function (PMF). * * @private * @param {number} x - input value * @returns {number} evaluated logPMF */ function negativeBinomialLogPMF( x ) { return logpmf( x, this.r, this.p ); } /** * Evaluates the moment-generating function (MGF). * * @private * @param {number} t - input value * @returns {number} evaluated MGF */ function negativeBinomialMGF( t ) { return mgf( t, this.r, this.p ); } /** * Evaluates the probability mass function (PMF). * * @private * @param {number} x - input value * @returns {number} evaluated PMF */ function negativeBinomialPMF( x ) { return pmf( x, this.r, this.p ); } /** * Evaluates the quantile function. * * @private * @param {Probability} p - input probability * @returns {number} evaluated quantile function */ function negativeBinomialQuantile( p ) { return quantile( p, this.r, this.p ); } // MAIN // /** * Negative binomial distribution constructor. * * @constructor * @param {PositiveNumber} [r=1.0] - number of successes until experiment is stopped * @param {Probability} [p=0.5] - success probability * @throws {TypeError} `r` must be a positive number * @throws {TypeError} `p` must be a number between 0 and 1 * @returns {NegativeBinomial} distribution instance * * @example * var nbinomial = new NegativeBinomial( 5.0, 0.1 ); * * var y = nbinomial.cdf( 10.0 ); * // returns ~0.013 * * var v = nbinomial.mode; * // returns 36.0 */ function NegativeBinomial() { var r; var p; if ( !(this instanceof NegativeBinomial) ) { if ( arguments.length === 0 ) { return new NegativeBinomial(); } return new NegativeBinomial( arguments[ 0 ], arguments[ 1 ] ); } if ( arguments.length ) { r = arguments[ 0 ]; p = arguments[ 1 ]; if ( !isPositive( r ) ) { throw new TypeError( format( 'invalid argument. Number of trials until experiment is stopped must be a positive number. Value: `%s`.', r ) ); } if ( !isProbability( p ) ) { throw new TypeError( format( 'invalid argument. Success probability must be a number between 0 and 1. Value: `%s`.', p ) ); } } else { r = 1.0; p = 0.5; } defineProperty( this, 'r', { 'configurable': false, 'enumerable': true, 'get': function get() { return r; }, 'set': function set( value ) { if ( !isPositive( value ) ) { throw new TypeError( format( 'invalid assignment. Must be a positive number. Value: `%s`.', value ) ); } r = value; } }); defineProperty( this, 'p', { 'configurable': false, 'enumerable': true, 'get': function get() { return p; }, 'set': function set( value ) { if ( !isProbability( value ) ) { throw new TypeError( format( 'invalid assignment. Must be a number on the interval: [0, 1]. Value: `%s`.', value ) ); } p = value; } }); return this; } /** * Negative binomial distribution excess kurtosis. * * @name kurtosis * @memberof NegativeBinomial.prototype * @type {number} * @see [kurtosis]{@link https://en.wikipedia.org/wiki/Kurtosis} * * @example * var nbinomial = new NegativeBinomial( 12.0, 0.4 ); * * var v = nbinomial.kurtosis; * // returns ~0.522 */ setReadOnlyAccessor( NegativeBinomial.prototype, 'kurtosis', function get() { return kurtosis( this.r, this.p ); }); /** * Negative binomial distribution expected value. * * @name mean * @memberof NegativeBinomial.prototype * @type {number} * @see [expected value]{@link https://en.wikipedia.org/wiki/Expected_value} * * @example * var nbinomial = new NegativeBinomial( 12.0, 0.4 ); * * var v = nbinomial.mean; * // returns ~18.0 */ setReadOnlyAccessor( NegativeBinomial.prototype, 'mean', function get() { return mean( this.r, this.p ); }); /** * Negative binomial distribution mode. * * @name mode * @memberof NegativeBinomial.prototype * @type {NonNegativeInteger} * @see [mode]{@link https://en.wikipedia.org/wiki/Mode_%28statistics%29} * * @example * var nbinomial = new NegativeBinomial( 12.0, 0.4 ); * * var v = nbinomial.mode; * // returns 16.0 */ setReadOnlyAccessor( NegativeBinomial.prototype, 'mode', function get() { return mode( this.r, this.p ); }); /** * Negative binomial distribution skewness. * * @name skewness * @memberof NegativeBinomial.prototype * @type {number} * @see [skewness]{@link https://en.wikipedia.org/wiki/Skewness} * * @example * var nbinomial = new NegativeBinomial( 12.0, 0.4 ); * * var v = nbinomial.skewness; * // returns ~0.596 */ setReadOnlyAccessor( NegativeBinomial.prototype, 'skewness', function get() { return skewness( this.r, this.p ); }); /** * Negative binomial distribution standard deviation. * * @name stdev * @memberof NegativeBinomial.prototype * @type {PositiveNumber} * @see [standard deviation]{@link https://en.wikipedia.org/wiki/Standard_deviation} * * @example * var nbinomial = new NegativeBinomial( 12.0, 0.4 ); * * var v = nbinomial.stdev; * // returns ~6.708 */ setReadOnlyAccessor( NegativeBinomial.prototype, 'stdev', function get() { return stdev( this.r, this.p ); }); /** * Negative binomial distribution variance. * * @name variance * @memberof NegativeBinomial.prototype * @type {PositiveNumber} * @see [variance]{@link https://en.wikipedia.org/wiki/Variance} * * @example * var nbinomial = new NegativeBinomial( 12.0, 0.4 ); * * var v = nbinomial.variance; * // returns ~45.0 */ setReadOnlyAccessor( NegativeBinomial.prototype, 'variance', function get() { return variance( this.r, this.p ); }); /** * Evaluates the cumulative distribution function (CDF). * * @name cdf * @memberof NegativeBinomial.prototype * @type {Function} * @param {number} x - input value * @returns {number} evaluated CDF * @see [cdf]{@link https://en.wikipedia.org/wiki/Cumulative_distribution_function} * * @example * var nbinomial = new NegativeBinomial( 4.0, 0.2 ); * * var v = nbinomial.cdf( 3.0 ); * // returns ~0.033 */ setReadOnly( NegativeBinomial.prototype, 'cdf', negativeBinomialCDF ); /** * Evaluates the natural logarithm of the probability mass function (PMF). * * @name logpmf * @memberof NegativeBinomial.prototype * @type {Function} * @param {number} x - input value * @returns {number} evaluated logPMF * @see [pmf]{@link https://en.wikipedia.org/wiki/Probability_mass_function} * * @example * var nbinomial = new NegativeBinomial( 4.0, 0.2 ); * * var v = nbinomial.logpmf( 9.0 ); * // returns ~-3.052 */ setReadOnly( NegativeBinomial.prototype, 'logpmf', negativeBinomialLogPMF ); /** * Evaluates the moment-generating function (MGF). * * @name mgf * @memberof NegativeBinomial.prototype * @type {Function} * @param {number} t - input value * @returns {number} evaluated MGF * @see [mgf]{@link https://en.wikipedia.org/wiki/Moment-generating_function} * * @example * var nbinomial = new NegativeBinomial( 4.0, 0.2 ); * * var v = nbinomial.mgf( 0.1 ); * // returns ~1.66 */ setReadOnly( NegativeBinomial.prototype, 'mgf', negativeBinomialMGF ); /** * Evaluates the probability mass function (PMF). * * @name pmf * @memberof NegativeBinomial.prototype * @type {Function} * @param {number} x - input value * @returns {number} evaluated PMF * @see [pmf]{@link https://en.wikipedia.org/wiki/Probability_mass_function} * * @example * var nbinomial = new NegativeBinomial( 4.0, 0.2 ); * * var v = nbinomial.pmf( 9.0 ); * // returns ~0.047 */ setReadOnly( NegativeBinomial.prototype, 'pmf', negativeBinomialPMF ); /** * Evaluates the quantile function. * * @name quantile * @memberof NegativeBinomial.prototype * @type {Function} * @param {Probability} p - input probability * @returns {number} evaluated quantile function * @see [quantile function]{@link https://en.wikipedia.org/wiki/Quantile_function} * * @example * var nbinomial = new NegativeBinomial( 4.0, 0.2 ); * * var v = nbinomial.quantile( 0.5 ); * // returns 15.0 */ setReadOnly( NegativeBinomial.prototype, 'quantile', negativeBinomialQuantile ); // EXPORTS // module.exports = NegativeBinomial;