npm package: @stdlib/stats-base-dists-degenerate-logpmf
Description: Natural logarithm of the probability mass function (PMF) for a degenerate distribution.
Author: The Stdlib Authors
Latest version: 0.3.2

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# Logarithm of Probability Mass Function

[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url] <!-- [![dependencies][dependencies-image]][dependencies-url] -->

> Evaluate the natural logarithm of the [probability mass function][pmf] (PMF) for a [degenerate distribution][degenerate-distribution].

<section class="intro">

</section>

<!-- /.intro -->

<section class="installation">

## Installation

```bash
npm install @stdlib/stats-base-dists-degenerate-logpmf
```

</section>

<section class="usage">

## Usage

```javascript
var logpmf = require( '@stdlib/stats-base-dists-degenerate-logpmf' );
```

#### logpmf( x, mu )

Evaluates the natural logarithm of the [PMF][pmf] for a [degenerate distribution][degenerate-distribution] centered at `mu`.

```javascript
var y = logpmf( 2.0, 8.0 );
// returns -Infinity

y = logpmf( 8.0, 8.0 );
// returns 0.0
```

#### logpmf.factory( mu )

Returns a function for evaluating the natural logarithm of the [PMF][pmf] of a [degenerate distribution][degenerate-distribution] centered at `mu`.

```javascript
var mylogpmf = logpmf.factory( 10.0 );

var y = mylogpmf( 10.0 );
// returns 0.0

y = mylogpmf( 5.0 );
// returns -Infinity

y = mylogpmf( 12.0 );
// returns -Infinity
```

</section>

<!-- /.usage -->

<section class="examples">

## Examples

<!-- eslint no-undef: "error" -->

```javascript
var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var logEachMap = require( '@stdlib/console-log-each-map' );
var logpmf = require( '@stdlib/stats-base-dists-degenerate-logpmf' );

var opts = {
    'dtype': 'float64'
};
var x = discreteUniform( 100, 0, 5, opts );
var mu = discreteUniform( 100, 0, 5, opts );

logEachMap( 'x: %d, µ: %d, ln(P(X=x;µ)): %0.4f', x, mu, logpmf );
```

</section>

<!-- /.examples -->

<!-- C interface documentation. -->

* * *

<section class="c">

## C APIs

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<section class="intro">

</section>

<!-- /.intro -->

<!-- C usage documentation. -->

<section class="usage">

### Usage

```c
#include "stdlib/stats/base/dists/degenerate/logpmf.h"
```

#### stdlib_base_dists_degenerate_logpmf( x, mu )

Evaluates the natural logarithm of the [probability mass function][pmf] (PMF) for a [degenerate distribution][degenerate-distribution].

```c
double out = stdlib_base_dists_degenerate_logpmf( 2.0, 3.0 );
// returns -Infinity
```

The function accepts the following arguments:

-   **x**: `[in] double` input value.
-   **mu**: `[in] double` constant value of the distribution.

```c
double stdlib_base_dists_degenerate_logpmf( const double x, const double mu );
```

</section>

<!-- /.usage -->

<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->

<section class="notes">

</section>

<!-- /.notes -->

<!-- C API usage examples. -->

<section class="examples">

### Examples

```c
#include "stdlib/stats/base/dists/degenerate/logpmf.h"
#include "stdlib/math/base/special/round.h"
#include <stdlib.h>
#include <stdio.h>

static double random_uniform( const double min, const double max ) {
    double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
    return min + ( v * ( max - min ) );
}

int main( void ) {
    double result;
    double mu;
    double x;
    int i;

    for ( i = 0; i < 10; i++ ) {
        x = stdlib_base_round( random_uniform( 0.0, 5.0 ) );
        mu = stdlib_base_round( random_uniform( 0.0, 5.0 ) );
        result = stdlib_base_dists_degenerate_logpmf( x, mu );
        printf( "x: %lf, µ: %lf, ln(P(X=x;µ)): %lf \n", x, mu, result );
    }
}
```

</section>

<!-- /.examples -->

</section>

<!-- /.c -->

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<section class="related">

</section>

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<section class="main-repo" >

* * *

## 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

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---

## License

See [LICENSE][stdlib-license].


## Copyright

Copyright &copy; 2016-2026. The Stdlib [Authors][stdlib-authors].

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[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/stats-base-dists-degenerate-logpmf/main/LICENSE

[pmf]: https://en.wikipedia.org/wiki/Probability_mass_function

[degenerate-distribution]: https://en.wikipedia.org/wiki/Degenerate_distribution

</section>

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