Mean

Gumbel distribution expected value.

The mean for a Gumbel random variable with location μ and scale β is

where γ is the Euler–Mascheroni constant.

Installation

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

Usage

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

mean( mu, beta )

Returns the expected value for a Gumbel distribution with location parameter mu and scale parameter beta.

var y = mean( 2.0, 1.0 );
// returns ~2.577

y = mean( 0.0, 1.0 );
// returns ~0.577

y = mean( -1.0, 4.0 );
// returns ~1.309

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

var y = mean( NaN, 1.0 );
// returns NaN

y = mean( 0.0, NaN );
// returns NaN

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

var y = mean( 0.0, 0.0 );
// returns NaN

y = mean( 0.0, -1.0 );
// returns NaN

Examples

var uniform = require( '@stdlib/random-array-uniform' );
var logEachMap = require( '@stdlib/console-log-each-map' );
var mean = require( '@stdlib/stats-base-dists-gumbel-mean' );

var opts = {
    'dtype': 'float64'
};
var beta = uniform( 10, 0.0, 20.0, opts );
var mu = uniform( 10, -5.0, 5.0, opts );

logEachMap( 'µ: %0.4f, β: %0.4f, E(X;µ,β): %0.4f', mu, beta, mean );

C APIs

Usage

#include "stdlib/stats/base/dists/gumbel/mean.h"

stdlib_base_dists_gumbel_mean( mu, beta )

Returns the expected value for a Gumbel distribution with location parameter mu and scale parameter beta.

double out = stdlib_base_dists_gumbel_mean( 0.0, 1.0 );
// returns ~0.577

The function accepts the following arguments:

• mu: [in] double location parameter.
• beta: [in] double scale parameter.

double stdlib_base_dists_gumbel_mean( const double mu, const double beta );

Examples

#include "stdlib/stats/base/dists/gumbel/mean.h"
#include <stdlib.h>
#include <stdio.h>

static double random_uniform( const double min, const double max ) {
    double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
    return min + ( v*(max-min) );
}

int main( void ) {
    double beta;
    double mu;
    double y;
    int i;

    for ( i = 0; i < 25; i++ ) {
        mu = random_uniform( 0.0, 10.0 );
        beta = random_uniform( 0.0, 10.0 );
        y = stdlib_base_dists_gumbel_mean( mu, beta );
        printf( "µ: %lf, β: %lf, E(X;µ,β): %lf\n", mu, beta, y );
    }
}

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 © 2016-2026. The Stdlib Authors.