@stdlib/stats-base-dists-lognormal-logpdf
v0.2.3TypeScript
Natural logarithm of the probability density function (PDF) for a lognormal distribution.
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Published by The Stdlib Authors
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Logarithm of Probability Density Function
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> Evaluate the natural logarithm of the probability density function (PDF) for a [lognormal][lognormal-distribution] distribution.
The [probability density function][pdf] (PDF) for a [lognormal][lognormal-distribution] random variable is
where mu is the location parameter and sigma > 0 is the scale parameter. According to the definition, the _natural logarithm_ of a random variable from a
[lognormal distribution][lognormal-distribution] follows a [normal distribution][normal-distribution].
Installation
``bash`
npm install @stdlib/stats-base-dists-lognormal-logpdf
Usage
`javascript`
var logpdf = require( '@stdlib/stats-base-dists-lognormal-logpdf' );
#### logpdf( x, mu, sigma )
Evaluates the natural logarithm of the [probability density function][pdf] (PDF) for a [lognormal][lognormal-distribution] distribution with parameters mu (location parameter) and sigma (scale parameter).
`javascript
var y = logpdf( 2.0, 0.0, 1.0 );
// returns ~-1.852
y = logpdf( 1.0, 0.0, 1.0 );
// returns ~-0.919
y = logpdf( 1.0, 3.0, 1.0 );
// returns ~-5.419
`
If provided NaN as any argument, the function returns NaN.
`javascript
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 NaN
`
If provided sigma <= 0, the function returns NaN.
`javascript
var y = logpdf( 2.0, 0.0, -1.0 );
// returns NaN
y = logpdf( 2.0, 0.0, 0.0 );
// returns NaN
`
#### logpdf.factory( mu, sigma )
Returns a function for evaluating the natural logarithm of the [probability density function][pdf] (PDF) of a [lognormal][lognormal-distribution] distribution with parameters mu (location parameter) and sigma (scale parameter).
`javascript
var mylogpdf = logpdf.factory( 4.0, 2.0 );
var y = mylogpdf( 10.0 );
// returns ~-4.275
y = mylogpdf( 2.0 );
// returns ~-3.672
`
Examples
`javascript
var uniform = require( '@stdlib/random-array-uniform' );
var logEachMap = require( '@stdlib/console-log-each-map' );
var logpdf = require( '@stdlib/stats-base-dists-lognormal-logpdf' );
var opts = {
'dtype': 'float64'
};
var x = uniform( 10, 0.0, 10.0, opts );
var mu = uniform( 10, -5.0, 5.0, opts );
var sigma = uniform( 10, 0.0, 20.0, opts );
logEachMap( 'x: %0.4f, µ: %0.4f, σ: %0.4f, ln(f(x;µ,σ)): %0.4f', x, mu, sigma, logpdf );
`
*
Notice
This package is part of [stdlib][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][stdlib], see the main project [repository][stdlib].
#### Community
[![Chat][chat-image]][chat-url]
---
License
See [LICENSE][stdlib-license].
Copyright
Copyright © 2016-2026. The Stdlib [Authors][stdlib-authors].
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[umd]: https://github.com/umdjs/umd
[es-module]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Modules
[deno-url]: https://github.com/stdlib-js/stats-base-dists-lognormal-logpdf/tree/deno
[deno-readme]: https://github.com/stdlib-js/stats-base-dists-lognormal-logpdf/blob/deno/README.md
[umd-url]: https://github.com/stdlib-js/stats-base-dists-lognormal-logpdf/tree/umd
[umd-readme]: https://github.com/stdlib-js/stats-base-dists-lognormal-logpdf/blob/umd/README.md
[esm-url]: https://github.com/stdlib-js/stats-base-dists-lognormal-logpdf/tree/esm
[esm-readme]: https://github.com/stdlib-js/stats-base-dists-lognormal-logpdf/blob/esm/README.md
[branches-url]: https://github.com/stdlib-js/stats-base-dists-lognormal-logpdf/blob/main/branches.md
[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/stats-base-dists-lognormal-logpdf/main/LICENSE
[lognormal-distribution]: https://en.wikipedia.org/wiki/Lognormal_distribution
[normal-distribution]: https://en.wikipedia.org/wiki/Normal_distribution
[pdf]: https://en.wikipedia.org/wiki/Probability_density_function