@stdlib/stats-base-dists-binomial-logpmf
v0.2.3TypeScript
Natural logarithm of the probability mass function (PMF) for a binomial distribution.
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Logarithm of Probability Mass Function
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> Evaluate the natural logarithm of the probability mass function (PMF) for a [binomial][binomial-distribution] distribution.
The [probability mass function][pmf] (PMF) for a [binomial][binomial-distribution] random variable is
where n is the number of trials and 0 <= p <= 1 is the success probability.
Installation
``bash`
npm install @stdlib/stats-base-dists-binomial-logpmf
Usage
`javascript`
var logpmf = require( '@stdlib/stats-base-dists-binomial-logpmf' );
#### logpmf( x, n, p )
Evaluates the natural logarithm of the [probability mass function][pmf] (PMF) for a [binomial][binomial-distribution] distribution with number of trials n and success probability p.
`javascript
var y = logpmf( 3.0, 20, 0.2 );
// returns ~-1.583
y = logpmf( 21.0, 20, 0.2 );
// returns -Infinity
y = logpmf( 5.0, 10, 0.4 );
// returns ~-1.606
y = logpmf( 0.0, 10, 0.4 );
// returns ~-5.108
`
If provided NaN as any argument, the function returns NaN.
`javascript
var y = logpmf( NaN, 20, 0.5 );
// returns NaN
y = logpmf( 0.0, NaN, 0.5 );
// returns NaN
y = logpmf( 0.0, 20, NaN );
// returns NaN
`
If provided a number of trials n which is not a nonnegative integer, the function returns NaN.
`javascript
var y = logpmf( 2.0, 1.5, 0.5 );
// returns NaN
y = logpmf( 2.0, -2.0, 0.5 );
// returns NaN
`
If provided a success probability p outside of [0,1], the function returns NaN.
`javascript
var y = logpmf( 2.0, 20, -1.0 );
// returns NaN
y = logpmf( 2.0, 20, 1.5 );
// returns NaN
`
#### logpmf.factory( n, p )
Returns a function for evaluating the [probability mass function][pmf] (PMF) of a [binomial][binomial-distribution] distribution with number of trials n and success probability p.
`javascript
var mylogpmf = logpmf.factory( 10, 0.5 );
var y = mylogpmf( 3.0 );
// returns ~-2.144
y = mylogpmf( 5.0 );
// returns ~-1.402
`
Examples
`javascript
var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var uniform = require( '@stdlib/random-array-uniform' );
var logEachMap = require( '@stdlib/console-log-each-map' );
var logpmf = require( '@stdlib/stats-base-dists-binomial-logpmf' );
var opts = {
'dtype': 'float64'
};
var x = discreteUniform( 10, 0, 20, opts );
var n = discreteUniform( 10, 0, 100, opts );
var p = uniform( 10, 0.0, 1.0, opts );
logEachMap( 'x: %0.4f, n: %0.4f, p: %0.4f, ln(P(X = x;n,p)): %0.4f', x, n, p, logpmf );
`
*
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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[deno-url]: https://github.com/stdlib-js/stats-base-dists-binomial-logpmf/tree/deno
[deno-readme]: https://github.com/stdlib-js/stats-base-dists-binomial-logpmf/blob/deno/README.md
[umd-url]: https://github.com/stdlib-js/stats-base-dists-binomial-logpmf/tree/umd
[umd-readme]: https://github.com/stdlib-js/stats-base-dists-binomial-logpmf/blob/umd/README.md
[esm-url]: https://github.com/stdlib-js/stats-base-dists-binomial-logpmf/tree/esm
[esm-readme]: https://github.com/stdlib-js/stats-base-dists-binomial-logpmf/blob/esm/README.md
[branches-url]: https://github.com/stdlib-js/stats-base-dists-binomial-logpmf/blob/main/branches.md
[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/stats-base-dists-binomial-logpmf/main/LICENSE
[binomial-distribution]: https://en.wikipedia.org/wiki/Binomial_distribution
[pmf]: https://en.wikipedia.org/wiki/Probability_mass_function