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# Logarithm of Probability Density Function

> [Gamma][gamma-distribution] distribution logarithm of probability density function (PDF).

<section class="intro">

The [probability density function][pdf] (PDF) for a [gamma][gamma-distribution] random variable is

<!-- <equation class="equation" label="eq:gamma_pdf" align="center" raw="f(x;\alpha,\beta)=\frac{\beta^\alpha}{\Gamma(\alpha)} x^{\alpha \,-\, 1} e^{- \beta x }" alt="Probability density function (PDF) for a Gamma distribution."> -->

<div class="equation" align="center" data-raw-text="f(x;\alpha,\beta)=\frac{\beta^\alpha}{\Gamma(\alpha)} x^{\alpha \,-\, 1} e^{- \beta x }" data-equation="eq:gamma_pdf">
    <img src="https://cdn.rawgit.com/stdlib-js/stdlib/7e0a95722efd9c771b129597380c63dc6715508b/lib/node_modules/@stdlib/stats/base/dists/gamma/logpdf/docs/img/equation_gamma_pdf.svg" alt="Probability density function (PDF) for a Gamma distribution.">
    <br>
</div>

<!-- </equation> -->

where `α > 0` is the shape parameter and `β > 0` is the rate parameter.

</section>

<!-- /.intro -->

<section class="usage">

## Usage

```javascript
var logpdf = require( '@stdlib/stats/base/dists/gamma/logpdf' );
```

#### logpdf( x, alpha, beta )

Evaluates the natural logarithm of the [probability density function][pdf] (PDF) for a [gamma][gamma-distribution] distribution with parameters `alpha` (shape parameter) and `beta` (rate parameter).

```javascript
var y = logpdf( 2.0, 0.5, 1.0 );
// returns ~-2.919

y = logpdf( 0.1, 1.0, 1.0 );
// returns ~-0.1

y = logpdf( -1.0, 4.0, 2.0 );
// returns -Infinity
```

If provided `NaN` as any argument, the function returns `NaN`.

```javascript
var y = logpdf( NaN, 1.0, 1.0 );
// returns NaN

y = logpdf( 0.0, NaN, 1.0 );
// returns NaN

y = logpdf( 0.0, 1.0, NaN );
// returns NaN
```

If provided `alpha < 0`, the function returns `NaN`.

```javascript
var y = logpdf( 2.0, -0.5, 1.0 );
// returns NaN
```

If provided `alpha = 0`, the function evaluates the logarithm of the [PDF][pdf] for a [degenerate distribution][degenerate-distribution] centered at `0`.

```javascript
var y = logpdf( 2.0, 0.0, 2.0 );
// returns -Infinity

y = logpdf( 0.0, 0.0, 2.0 );
// returns Infinity
```

If provided `beta <= 0`, the function returns `NaN`.

```javascript
var y = logpdf( 2.0, 1.0, 0.0 );
// returns NaN

y = logpdf( 2.0, 1.0, -1.0 );
// returns NaN
```

#### logpdf.factory( alpha, beta )

Returns a `function` for evaluating the natural logarithm of the [PDF][pdf] for a [gamma][gamma-distribution]  distribution with parameters `alpha` (shape parameter) and `beta` (rate parameter).

```javascript
var mylogpdf = logpdf.factory( 3.0, 1.5 );

var y = mylogpdf( 1.0 );
// returns ~-0.977

y = mylogpdf( 4.0 );
// returns ~-2.704
```

</section>

<!-- /.usage -->

<section class="examples">

## Examples

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

```javascript
var randu = require( '@stdlib/random/base/randu' );
var logpdf = require( '@stdlib/stats/base/dists/gamma/logpdf' );

var alpha;
var beta;
var x;
var y;
var i;

for ( i = 0; i < 10; i++ ) {
    x = randu() * 3.0;
    alpha = randu() * 5.0;
    beta = randu() * 5.0;
    y = logpdf( x, alpha, beta );
    console.log( 'x: %d, α: %d, β: %d, ln(f(x;α,β)): %d', x.toFixed( 4 ), alpha.toFixed( 4 ), beta.toFixed( 4 ), y.toFixed( 4 ) );
}
```

</section>

<!-- /.examples -->

<section class="links">

[gamma-distribution]: https://en.wikipedia.org/wiki/Gamma_distribution

[pdf]: https://en.wikipedia.org/wiki/Probability_density_function

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

</section>

<!-- /.links -->
