Gamma

Usage

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 0.0

By 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 0.5

gamma

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 3.0

gamma.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 3.0

Computed Properties

Gamma.prototype.entropy

Returns the differential entropy.

var gamma = new Gamma( 4.0, 12.0 );

var entropy = gamma.entropy;
// returns ~-0.462

Gamma.prototype.kurtosis

Returns the excess kurtosis.

var gamma = new Gamma( 4.0, 12.0 );

var kurtosis = gamma.kurtosis;
// returns 1.5

Gamma.prototype.mean

Returns the expected value.

var gamma = new Gamma( 4.0, 12.0 );

var mu = gamma.mean;
// returns ~0.333

Gamma.prototype.mode

Returns the mode.

var gamma = new Gamma( 4.0, 12.0 );

var mode = gamma.mode;
// returns 0.25

Gamma.prototype.skewness

Returns the skewness.

var gamma = new Gamma( 4.0, 12.0 );

var skewness = gamma.skewness;
// returns 1.0

Gamma.prototype.stdev

Returns the standard deviation.

var gamma = new Gamma( 4.0, 12.0 );

var s = gamma.stdev;
// returns ~0.167

Gamma.prototype.variance

Returns the variance.

var gamma = new Gamma( 4.0, 12.0 );

var s2 = gamma.variance;
// returns ~0.028

Methods

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 ~0.594

Gamma.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 ~-0.521

Gamma.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 ~-0.651

Gamma.prototype.mgf( t )

Evaluates the moment-generating function (MGF).

var gamma = new Gamma( 2.0, 4.0 );

var y = gamma.mgf( 0.5 );
// returns ~1.306

Gamma.prototype.pdf( x )

Evaluates the probability density function (PDF).

var gamma = new Gamma( 2.0, 4.0 );

var y = gamma.pdf( 0.8 );
// returns ~0.522

Gamma.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 NaN