@stdlib/stats-base-dists-weibull-logpdf
v0.2.2
Published
Weibull distribution logarithm of probability density function (PDF).
Downloads
949
Readme
Logarithm of Probability Density Function
Weibull distribution logarithm of probability density function (PDF).
The probability density function (PDF) for a Weibull random variable is
where lambda > 0
and k > 0
are the respective scale and shape parameters of the distribution.
Installation
npm install @stdlib/stats-base-dists-weibull-logpdf
Usage
var logpdf = require( '@stdlib/stats-base-dists-weibull-logpdf' );
logpdf( x, k, lambda )
Evaluates the logarithm of the probability density function (PDF) for a Weibull distribution with shape parameter k
and scale parameter lambda
.
var y = logpdf( 2.0, 1.0, 0.5 );
// returns ~-3.307
y = logpdf( -1.0, 4.0, 2.0 );
// returns -Infinity
If provided NaN
as any argument, the function returns NaN
.
var y = logpdf( NaN, 1.0, 1.0 );
// returns NaN
y = logpdf( 0.0, NaN, 1.0 );
// returns NaN
y = logpdf( 0.0, 1.0, NaN );
// returns NaN
If provided k <= 0
, the function returns NaN
.
var y = logpdf( 2.0, 0.0, 1.0 );
// returns NaN
y = logpdf( 2.0, -1.0, 1.0 );
// returns NaN
If provided lambda <= 0
, the function returns NaN
.
var y = logpdf( 2.0, 1.0, 0.0 );
// returns NaN
y = logpdf( 2.0, 1.0, -1.0 );
// returns NaN
logpdf.factory( k, lambda )
Returns a function
for evaluating the logarithm of the PDF for a Weibull distribution with shape parameter k
and scale parameter lambda
.
var mylogpdf = logpdf.factory( 2.0, 10.0 );
var y = mylogpdf( 12.0 );
// returns ~-2.867
y = mylogpdf( 5.0 );
// returns ~-2.553
Notes
- In virtually all cases, using the
logpdf
orlogcdf
functions is preferable to manually computing the logarithm of thepdf
orcdf
, respectively, since the latter is prone to overflow and underflow.
Examples
var randu = require( '@stdlib/random-base-randu' );
var logpdf = require( '@stdlib/stats-base-dists-weibull-logpdf' );
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 = logpdf( x, k, lambda );
console.log( 'x: %d, k: %d, λ: %d, ln(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.
Copyright
Copyright © 2016-2024. The Stdlib Authors.