@stdlib/stats
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Standard library statistical functions.
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# Probability Mass Function
> [Poisson][poisson-distribution] distribution [probability mass function][pmf] (PMF).
<section class="intro">
The [probability mass function][pmf] (PMF) for a [Poisson][poisson-distribution] random variable is
<!-- <equation class="equation" label="eq:poisson_pmf" align="center" raw="f(x;\lambda)=P(X=x;\lambda)=\begin{cases} \tfrac{\lambda^x}{x!}e^{-\lambda} & \text{ for } x = 0,1,2,\ldots \\ 0 & \text{ otherwise} \end{cases}" alt="Probability mass function (PMF) for a Poisson distribution."> -->
<div class="equation" align="center" data-raw-text="f(x;\lambda)=P(X=x;\lambda)=\begin{cases} \tfrac{\lambda^x}{x!}e^{-\lambda} & \text{ for } x = 0,1,2,\ldots \\ 0 & \text{ otherwise} \end{cases}" data-equation="eq:poisson_pmf">
<img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@51534079fef45e990850102147e8945fb023d1d0/lib/node_modules/@stdlib/stats/base/dists/poisson/pmf/docs/img/equation_poisson_pmf.svg" alt="Probability mass function (PMF) for a Poisson distribution.">
<br>
</div>
<!-- </equation> -->
where `lambda > 0` is the mean parameter.
</section>
<!-- /.intro -->
<section class="usage">
## Usage
```javascript
var pmf = require( '@stdlib/stats/base/dists/poisson/pmf' );
```
#### pmf( x, lambda )
Evaluates the [probability mass function][pmf] (PMF) of a [Poisson][poisson-distribution] distribution with mean parameter `lambda`.
```javascript
var y = pmf( 4.0, 3.0 );
// returns ~0.168
y = pmf( 1.0, 3.0 );
// returns ~0.149
y = pmf( -1.0, 2.0 );
// returns 0.0
```
If provided `NaN` as any argument, the function returns `NaN`.
```javascript
var y = pmf( NaN, 2.0 );
// returns NaN
y = pmf( 0.0, NaN );
// returns NaN
```
If provided a negative mean parameter `lambda`, the function returns `NaN`.
```javascript
var y = pmf( 2.0, -1.0 );
// returns NaN
y = pmf( 4.0, -2.0 );
// returns NaN
```
If provided `lambda = 0`, the function evaluates the [PMF][pmf] of a [degenerate distribution][degenerate-distribution] centered at `0.0`.
```javascript
var y = pmf( 2.0, 0.0 );
// returns 0.0
y = pmf( 0.0, 0.0 );
// returns 1.0
```
#### pmf.factory( lambda )
Returns a function for evaluating the [probability mass function][pmf] (PMF) of a [Poisson][poisson-distribution] distribution with mean parameter `lambda`.
```javascript
var mypmf = pmf.factory( 1.0 );
var y = mypmf( 3.0 );
// returns ~0.061
y = mypmf( 1.0 );
// returns ~0.368
```
</section>
<!-- /.usage -->
<section class="examples">
## Examples
<!-- eslint no-undef: "error" -->
```javascript
var randu = require( '@stdlib/random/base/randu' );
var round = require( '@stdlib/math/base/special/round' );
var pmf = require( '@stdlib/stats/base/dists/poisson/pmf' );
var lambda;
var x;
var y;
var i;
for ( i = 0; i < 10; i++ ) {
x = round( randu() * 10.0 );
lambda = randu() * 10.0;
y = pmf( x, lambda );
console.log( 'x: %d, λ: %d, P(X=x;λ): %d', x, lambda.toFixed( 4 ), y.toFixed( 4 ) );
}
```
</section>
<!-- /.examples -->
<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
<section class="related">
</section>
<!-- /.related -->
<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
<section class="links">
[degenerate-distribution]: https://en.wikipedia.org/wiki/Degenerate_distribution
[poisson-distribution]: https://en.wikipedia.org/wiki/Poisson_distribution
[pmf]: https://en.wikipedia.org/wiki/Probability_mass_function
</section>
<!-- /.links -->