npm package: @stdlib/stats-base-dists-bernoulli-mode
Description: Bernoulli distribution mode.
Author: The Stdlib Authors
Latest version: 0.3.1

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<details>
  <summary>
    About stdlib...
  </summary>
  <p>We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.</p>
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</details>

# Mode

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

> [Bernoulli][bernoulli-distribution] distribution [mode][mode].

<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->

<section class="intro">

The [mode][mode] for a [Bernoulli][bernoulli-distribution] random variable is

<!-- <equation class="equation" label="eq:bernoulli_mode" align="center" raw="\operatorname{Mode}\left( X \right) = \begin{cases} 0 & \text{if } p < 1/2 \\ 0, 1 &\text{if } p = 1/2 \\ 1 & \text{if } p > 1/2 \end{cases}" alt="Mode for a Bernoulli distribution."> -->

<div class="equation" align="center" data-raw-text="\operatorname{Mode}\left( X \right) = \begin{cases} 0 &amp; \text{if } p &lt; 1/2 \\ 0, 1 &amp;\text{if } p = 1/2 \\ 1 &amp; \text{if } p &gt; 1/2 \end{cases}" data-equation="eq:bernoulli_mode">
    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@e1fbdee688c5409e4cc6b0cd06d90b1cd2abd67c/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mode/docs/img/equation_bernoulli_mode.svg" alt="Mode for a Bernoulli distribution.">
    <br>
</div>

<!-- </equation> -->

where `p` is the success probability.

</section>

<!-- /.intro -->

<!-- Package usage documentation. -->

<section class="installation">

## Installation

```bash
npm install @stdlib/stats-base-dists-bernoulli-mode
```

</section>

<section class="usage">

## Usage

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

#### mode( p )

Returns the [mode][mode] of a [Bernoulli][bernoulli-distribution] distribution with success probability `p`.

```javascript
var v = mode( 0.1 );
// returns 0

v = mode( 0.5 );
// returns 0

v = mode( 0.8 );
// returns 1
```

If provided a success probability `p` outside of `[0,1]`, the function returns `NaN`.

```javascript
var v = mode( NaN );
// returns NaN

v = mode( 1.5 );
// returns NaN

v = mode( -1.0 );
// returns NaN
```

</section>

<!-- /.usage -->

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

<section class="notes">

## Notes

-   For `p = 0.5`, the mode is either `0` or `1`. This implementation returns `0` for `p = 0.5`.

</section>

<!-- /.notes -->

<!-- Package usage examples. -->

<section class="examples">

## Examples

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

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

var opts = {
    'dtype': 'float64'
};
var p = uniform( 25, 0.0, 1.0, opts );

logEachMap( 'p: %0.4f, mode(X;p): %0.4f', p, mode );
```

</section>

<!-- /.examples -->

<!-- C interface documentation. -->

* * *

<section class="c">

## C APIs

<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->

<section class="intro">

</section>

<!-- /.intro -->

<!-- C usage documentation. -->

<section class="usage">

### Usage

```c
#include "stdlib/stats/base/dists/bernoulli/mode.h"
```

#### stdlib_base_dists_bernoulli_mode( p )

Returns the [mode][mode] of a [Bernoulli][bernoulli-distribution] distribution with success probability `p`.

```c
double out = stdlib_base_dists_bernoulli_mode( 0.1 );
// returns 0
```

The function accepts the following arguments:

-   **p**: `[in] double` success probability.

```c
double stdlib_base_dists_bernoulli_mode( const double p );
```

</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/bernoulli/mode.h"
#include <stdlib.h>
#include <stdio.h>

int main( void ) {
    double p;
    double y;
    int i;

    for ( i = 0; i < 25; i++ ) {
        p = (double)rand() / ( (double)RAND_MAX + 1.0 );
        y = stdlib_base_dists_bernoulli_mode( p );
        printf( "x: %lf, mode(X;p): %lf\n", p, y );
    }
}
```

</section>

<!-- /.examples -->

</section>

<!-- /.c -->

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<section class="references">

</section>

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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

[![Chat][chat-image]][chat-url]

---

## License

See [LICENSE][stdlib-license].


## Copyright

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

</section>

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

[bernoulli-distribution]: https://en.wikipedia.org/wiki/Bernoulli_distribution

[mode]: https://en.wikipedia.org/wiki/Mode_%28statistics%29

</section>

<!-- /.links -->