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  • License Apache-2.0

Gamma distribution mode.

Package Exports

  • @stdlib/stats-base-dists-gamma-mode

This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (@stdlib/stats-base-dists-gamma-mode) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.

Readme

Mode

Gamma distribution mode.

The mode for a gamma random variable is

Mode for a gamma distribution.

when shape α >= 1 and rate β > 0. For other parameter values, the mode is not defined.

Installation

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

Usage

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

mode( alpha, beta )

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

var v = mode( 1.0, 1.0 );
// returns 0.0

v = mode( 4.0, 12.0 );
// returns 0.25

v = mode( 8.0, 2.0 );
// returns 3.5

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

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

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

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

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

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

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

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

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

Examples

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

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 = mode( alpha, beta );
    console.log( 'α: %d, β: %d, mode(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.


License

See LICENSE.

Copyright © 2016-2021. The Stdlib Authors.