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@stdlib/stats-base-dists-lognormal-median

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  • License Apache-2.0

Lognormal distribution median.

Package Exports

  • @stdlib/stats-base-dists-lognormal-median
  • @stdlib/stats-base-dists-lognormal-median/lib/index.js

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-lognormal-median) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.

Readme

Median

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Lognormal distribution median.

The median for a lognormal random variable with location parameter μ and scale parameter σ > 0 is

Median for a lognormal distribution.

According to the definition, the natural logarithm of a random variable from a lognormal distribution follows a normal distribution.

Installation

npm install @stdlib/stats-base-dists-lognormal-median

Usage

var median = require( '@stdlib/stats-base-dists-lognormal-median' );

median( mu, sigma )

Returns the median for a lognormal distribution with location mu and scale sigma.

var y = median( 2.0, 1.0 );
// returns ~7.389

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

y = median( -1.0, 4.0 );
// returns ~0.368

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

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

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

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

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

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

Examples

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

var sigma;
var mu;
var y;
var i;

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

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License

See LICENSE.

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