Mean

Logistic distribution expected value.

The expected value for a logistic random variable with location μ and scale s > 0 is

\mathbb{E}\left[ X \right] = \mu

Installation

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

Alternatively,

To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm branch (see README).
If you are using Deno, visit the deno branch (see README for usage intructions).
For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (see README).

The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.

To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.

Usage

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

mean( mu, s )

Returns the expected value for a logistic distribution with location parameter mu and scale parameter s.

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

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

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

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 s <= 0, the function returns NaN.

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

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

Examples

var randu = require( '@stdlib/random-base-randu' );
var mean = require( '@stdlib/stats-base-dists-logistic-mean' );

var mu;
var s;
var y;
var i;

for ( i = 0; i < 10; i++ ) {
    mu = ( randu()*10.0 ) - 5.0;
    s = randu() * 20.0;
    y = mean( mu, s );
    console.log( 'µ: %d, s: %d, E(X;µ,s): %d', mu.toFixed( 4 ), s.toFixed( 4 ), y.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.