@stdlib/stats-base-dists-gamma-ctor
v0.2.2
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Gamma distribution constructor.
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Gamma
Gamma distribution constructor.
Installation
npm install @stdlib/stats-base-dists-gamma-ctorUsage
var Gamma = require( '@stdlib/stats-base-dists-gamma-ctor' );Gamma( [alpha, beta] )
Returns a gamma distribution object.
var gamma = new Gamma();
var mode = gamma.mode;
// returns 0.0By default, alpha = 1.0 and beta = 1.0. To create a distribution having a different alpha (shape parameter) and beta (rate parameter), provide the corresponding arguments.
var gamma = new Gamma( 2.0, 4.0 );
var mu = gamma.mean;
// returns 0.5gamma
A gamma distribution object has the following properties and methods...
Writable Properties
gamma.alpha
Shape parameter of the distribution. alpha must be a positive number.
var gamma = new Gamma();
var alpha = gamma.alpha;
// returns 1.0
gamma.alpha = 3.0;
alpha = gamma.alpha;
// returns 3.0gamma.beta
Rate parameter of the distribution. beta must be a positive number.
var gamma = new Gamma( 2.0, 4.0 );
var b = gamma.beta;
// returns 4.0
gamma.beta = 3.0;
b = gamma.beta;
// returns 3.0Computed Properties
Gamma.prototype.entropy
Returns the differential entropy.
var gamma = new Gamma( 4.0, 12.0 );
var entropy = gamma.entropy;
// returns ~-0.462Gamma.prototype.kurtosis
Returns the excess kurtosis.
var gamma = new Gamma( 4.0, 12.0 );
var kurtosis = gamma.kurtosis;
// returns 1.5Gamma.prototype.mean
Returns the expected value.
var gamma = new Gamma( 4.0, 12.0 );
var mu = gamma.mean;
// returns ~0.333Gamma.prototype.mode
Returns the mode.
var gamma = new Gamma( 4.0, 12.0 );
var mode = gamma.mode;
// returns 0.25Gamma.prototype.skewness
Returns the skewness.
var gamma = new Gamma( 4.0, 12.0 );
var skewness = gamma.skewness;
// returns 1.0Gamma.prototype.stdev
Returns the standard deviation.
var gamma = new Gamma( 4.0, 12.0 );
var s = gamma.stdev;
// returns ~0.167Gamma.prototype.variance
Returns the variance.
var gamma = new Gamma( 4.0, 12.0 );
var s2 = gamma.variance;
// returns ~0.028Methods
Gamma.prototype.cdf( x )
Evaluates the cumulative distribution function (CDF).
var gamma = new Gamma( 2.0, 4.0 );
var y = gamma.cdf( 0.5 );
// returns ~0.594Gamma.prototype.logcdf( x )
Evaluates the natural logarithm of the cumulative distribution function (CDF).
var gamma = new Gamma( 2.0, 4.0 );
var y = gamma.logcdf( 0.5 );
// returns ~-0.521Gamma.prototype.logpdf( x )
Evaluates the natural logarithm of the probability density function (PDF).
var gamma = new Gamma( 2.0, 4.0 );
var y = gamma.logpdf( 0.8 );
// returns ~-0.651Gamma.prototype.mgf( t )
Evaluates the moment-generating function (MGF).
var gamma = new Gamma( 2.0, 4.0 );
var y = gamma.mgf( 0.5 );
// returns ~1.306Gamma.prototype.pdf( x )
Evaluates the probability density function (PDF).
var gamma = new Gamma( 2.0, 4.0 );
var y = gamma.pdf( 0.8 );
// returns ~0.522Gamma.prototype.quantile( p )
Evaluates the quantile function at probability p.
var gamma = new Gamma( 2.0, 4.0 );
var y = gamma.quantile( 0.5 );
// returns ~0.42
y = gamma.quantile( 1.9 );
// returns NaNExamples
var Gamma = require( '@stdlib/stats-base-dists-gamma-ctor' );
var gamma = new Gamma( 2.0, 4.0 );
var mu = gamma.mean;
// returns 0.5
var mode = gamma.mode;
// returns 0.25
var s2 = gamma.variance;
// returns 0.125
var y = gamma.cdf( 0.8 );
// returns ~0.829Notice
This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
Community
License
See LICENSE.
Copyright
Copyright © 2016-2024. The Stdlib Authors.
