Mean

Gamma distribution expected value.

The expected value for a gamma random variable is

where α > 0 is the shape parameter β > 0 is the rate parameter.

Installation

npm install @stdlib/stats-base-dists-gamma-mean

Usage

var mean = require( '@stdlib/stats-base-dists-gamma-mean' );

mean( alpha, beta )

Returns the expected value of a gamma distribution with parameters alpha (shape parameter) and beta (rate parameter).

var v = mean( 1.0, 1.0 );
// returns 1.0

v = mean( 4.0, 12.0 );
// returns ~0.333

v = mean( 8.0, 2.0 );
// returns 4.0

If provided NaN as any argument, the function returns NaN.

var v = mean( NaN, 2.0 );
// returns NaN

v = mean( 2.0, NaN );
// returns NaN

If provided alpha <= 0, the function returns NaN.

var v = mean( 0.0, 1.0 );
// returns NaN

v = mean( -1.0, 1.0 );
// returns NaN

If provided beta <= 0, the function returns NaN.

var v = mean( 1.0, 0.0 );
// returns NaN

v = mean( 1.0, -1.0 );
// returns NaN

Examples

var randu = require( '@stdlib/random-base-randu' );
var EPS = require( '@stdlib/constants-float64-eps' );
var mean = require( '@stdlib/stats-base-dists-gamma-mean' );

var alpha;
var beta;
var v;
var i;

for ( i = 0; i < 10; i++ ) {
    alpha = ( randu()*10.0 ) + EPS;
    beta = ( randu()*10.0 ) + EPS;
    v = mean( alpha, beta );
    console.log( 'α: %d, β: %d, E(X;α,β): %d', alpha.toFixed( 4 ), beta.toFixed( 4 ), v.toFixed( 4 ) );
}

Notice

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.