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@stdlib/stats-base-dists-frechet-stdev

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Fréchet distribution standard deviation.

Package Exports

  • @stdlib/stats-base-dists-frechet-stdev

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Standard Deviation

NPM version Build Status Coverage Status dependencies

Fréchet distribution standard deviation.

The standard deviation for a Fréchet random variable shape α > 0, scale s > 0, and location parameter m is

Standard deviation for a Fréchet distribution.

where Γ is the gamma function.

Installation

npm install @stdlib/stats-base-dists-frechet-stdev

Usage

var stdev = require( '@stdlib/stats-base-dists-frechet-stdev' );

stdev( alpha, s, m )

Returns the standard deviation for a Fréchet distribution with shape alpha > 0, scale s > 0, and location parameter m.

var y = stdev( 3.0, 1.0, 1.0 );
// returns ~0.919

y = stdev( 3.0, 2.0, -3.0 );
// returns ~1.839

y = stdev( 5.0, 1.0, 2.0 );
// returns ~0.366

If 0 < alpha <= 2.0, the function returns +Infinity.

var y = stdev( 1.0, 1.0, 1.0 );
// returns Infinity

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

var y = stdev( NaN, 1.0, -2.0 );
// returns NaN

y = stdev( 1.0, NaN, -2.0 );
// returns NaN

y = stdev( 1.0, 1.0, NaN );
// returns NaN

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

var y = stdev( 0.0, 3.0, 2.0 );
// returns NaN

y = stdev( 0.0, -1.0, 2.0 );
// returns NaN

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

var y = stdev( 1.0, 0.0, 2.0 );
// returns NaN

y = stdev( 1.0, -1.0, 2.0 );
// returns NaN

Examples

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

var alpha;
var m;
var s;
var y;
var i;

for ( i = 0; i < 10; i++ ) {
    alpha = ( randu()*20.0 ) + EPS;
    s = ( randu()*20.0 ) + EPS;
    m = ( randu()*20.0 ) - 40.0;
    y = stdev( alpha, s, m );
    console.log( 'α: %d, s: %d, m: %d, SD(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.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.


License

See LICENSE.

Copyright © 2016-2021. The Stdlib Authors.