@stdlib/stats-base-dists-laplace-logpdf
v0.2.2
Published
Laplace distribution logarithm of probability density function (PDF).
Readme
Logarithm of Probability Density Function
Laplace distribution logarithm of probability density function (PDF).
The probability density function (PDF) for a Laplace random variable is
where mu is the location parameter and b > 0 is the scale parameter (also called diversity).
Installation
npm install @stdlib/stats-base-dists-laplace-logpdfUsage
var logpdf = require( '@stdlib/stats-base-dists-laplace-logpdf' );logpdf( x, mu, b )
Evaluates the logarithm of the probability density function (PDF) for a Laplace distribution with parameters mu (location parameter) and b > 0 (scale parameter).
var y = logpdf( 2.0, 0.0, 1.0 );
// returns ~-2.693
y = logpdf( -1.0, 2.0, 3.0 );
// returns ~-2.792
y = logpdf( 2.5, 2.0, 3.0 );
// returns ~-1.958If provided NaN as any argument, the function returns NaN.
var y = logpdf( NaN, 0.0, 1.0 );
// returns NaN
y = logpdf( 0.0, NaN, 1.0 );
// returns NaN
y = logpdf( 0.0, 0.0, NaN );
// returns NaNIf provided b <= 0, the function returns NaN.
var y = logpdf( 2.0, 0.0, -1.0 );
// returns NaN
y = logpdf( 2.0, 8.0, 0.0 );
// returns NaNlogpdf.factory( mu, b )
Return a function for evaluating the logarithm of the PDF for a Laplace distribution with parameters mu (location parameter) and b > 0 (scale parameter).
var mylogpdf = logpdf.factory( 10.0, 2.0 );
var y = mylogpdf( 10.0 );
// returns ~-1.386
y = mylogpdf( 5.0 );
// returns ~-3.886
y = mylogpdf( 12.0 );
// returns ~-2.386Notes
- In virtually all cases, using the
logpdforlogcdffunctions is preferable to manually computing the logarithm of thepdforcdf, 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-laplace-logpdf' );
var mu;
var b;
var x;
var y;
var i;
for ( i = 0; i < 100; i++ ) {
x = randu() * 10.0;
mu = randu() * 10.0;
b = randu() * 10.0;
y = logpdf( x, mu, b );
console.log( 'x: %d, µ: %d, b: %d, ln(f(x;µ,b)): %d', x.toFixed( 4 ), mu.toFixed( 4 ), b.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.
