README

Probability Density Function

Weibull distribution probability density function (PDF).

The probability density function (PDF) for a Weibull random variable is

Probability density function (PDF) for a Weibull distribution.

where lambda > 0 and k > 0 are the respective scale and shape parameters of the distribution.

Installation

npm install @stdlib/stats-base-dists-weibull-pdf

Usage

var pdf = require( '@stdlib/stats-base-dists-weibull-pdf' );

pdf( x, k, lambda )

Evaluates the probability density function (PDF) for a Weibull distribution with shape parameter k and scale parameter lambda.

var y = pdf( 2.0, 1.0, 0.5 );
// returns ~0.037

y = pdf( -1.0, 4.0, 2.0 );
// returns 0.0

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

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

y = pdf( 0.0, NaN, 1.0 );
// returns NaN

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

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

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

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

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

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

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

pdf.factory( k, lambda )

Returns a function for evaluating the PDF for a Weibull distribution with shape parameter k and scale parameter lambda.

var mypdf = pdf.factory( 2.0, 10.0 );

var y = mypdf( 12.0 );
// returns ~0.057

y = mypdf( 5.0 );
// returns ~0.078

Examples

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

var lambda;
var k;
var x;
var y;
var i;

for ( i = 0; i < 10; i++ ) {
    x = randu() * 10.0;
    lambda = randu() * 10.0;
    k = randu() * 10.0;
    y = pdf( x, lambda, k );
    console.log( 'x: %d, k: %d, λ: %d, f(x;k,λ): %d', x.toFixed( 4 ), k.toFixed( 4 ), lambda.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.

Community

License

See LICENSE.

@stdlib/stats-base-dists-weibull-pdf

Usage no npm install needed!