@stdlib/stats/base/dists/truncated-normal/pdf/README.md

Standard library statistical functions.

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# Probability Density Function

> [Truncated normal][truncated-normal-distribution] distribution probability density function (PDF).

<section class="intro">

A normally distributed random variable `X` conditional on `a < X < b` is called a [truncated normal][truncated-normal-distribution] distribution.
The [probability density function][pdf] (PDF) for a [truncated normal][truncated-normal-distribution] random variable is

<!-- <equation class="equation" label="eq:truncated_normal_pdf" align="center" raw="f(x;\mu,\sigma,a,b) =  \begin{cases} \frac{\frac{1}{\sigma}\phi(\frac{x - \mu}{\sigma})}{\Phi(\frac{b - \mu}{\sigma}) - \Phi(\frac{a - \mu}{\sigma}) } & \text{ if } a < x < b \\ 0 & \text{ otherwise } \end{cases}" alt="Probability density function (PDF) for a truncated normal distribution."> -->

<div class="equation" align="center" data-raw-text="f(x;\mu,\sigma,a,b) =  \begin{cases} \frac{\frac{1}{\sigma}\phi(\frac{x - \mu}{\sigma})}{\Phi(\frac{b - \mu}{\sigma}) - \Phi(\frac{a - \mu}{\sigma}) } &amp; \text{ if } a &lt; x &lt; b \\ 0 &amp; \text{ otherwise } \end{cases}" data-equation="eq:truncated_normal_pdf">
    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@51534079fef45e990850102147e8945fb023d1d0/lib/node_modules/@stdlib/stats/base/dists/truncated-normal/pdf/docs/img/equation_truncated_normal_pdf.svg" alt="Probability density function (PDF) for a truncated normal distribution.">
    <br>
</div>

<!-- </equation> -->

where `Phi` and `phi` denote the [cumulative distribution function][cdf] and [density function][pdf] of the [normal][normal-distribution] distribution, respectively, `mu` is the location  and `sigma > 0` is the scale parameter of the distribution. `a` and `b` are the minimum and maximum support.

</section>

<!-- /.intro -->

<section class="usage">

## Usage

```javascript
var pdf = require( '@stdlib/stats/base/dists/truncated-normal/pdf' );
```

#### pdf( x, a, b, mu, sigma )

Evaluates the probability density function (PDF) for a [truncated normal][truncated-normal-distribution] distribution with lower limit `a`, upper limit `b`, location parameter `mu`, and scale parameter `sigma`.

```javascript
var y = pdf( 0.9, 0.0, 1.0, 0.0, 1.0 );
// returns ~0.7795

y = pdf( 0.9, 0.0, 1.0, 0.5, 1.0 );
// returns ~0.9617

y = pdf( 0.9, -1.0, 1.0, 0.5, 1.0 );
// returns ~0.5896

y = pdf( 1.4, 0.0, 1.0, 0.0, 1.0 );
// returns 0.0

y = pdf( -0.9, 0.0, 1.0, 0.0, 1.0 );
// returns 0.0
```

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

```javascript
var y = pdf( NaN, 0.0, 1.0, 0.5, 2.0 );
// returns NaN

y = pdf( 0.0, NaN, 1.0, 0.5, 2.0 );
// returns NaN

y = pdf( 0.0, 0.0, NaN, 0.5, 2.0 );
// returns NaN

y = pdf( 0.6, 0.0, 1.0, NaN, 2.0 );
// returns NaN

y = pdf( 0.6, 0.0, 1.0, 0.5, NaN );
// returns NaN
```

#### pdf.factory( a, b, mu, sigma )

Returns a function for evaluating the [probability density function][pdf] (PDF) for a [truncated normal][truncated-normal-distribution] distribution.

```javascript
var myPDF = pdf.factory( 0.0, 1.0, 0.0, 1.0 );
var y = myPDF( 0.8 );
// returns ~0.849

myPDF = pdf.factory( 0.0, 1.0, 0.5, 1.0 );
y = myPDF( 0.8 );
// returns ~0.996
```

</section>

<!-- /.usage -->

<section class="examples">

## Examples

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

```javascript
var randu = require( '@stdlib/random/base/randu' );
var pdf = require( '@stdlib/stats/base/dists/truncated-normal/pdf' );

var sigma;
var mu;
var a;
var b;
var x;
var y;
var i;

for ( i = 0; i < 25; i++ ) {
    a = ( randu() * 80.0 ) - 40.0;
    b = a + ( randu() * 80.0 );
    x = ( randu() * 40.0 ) + a;
    mu = ( randu() * 20.0 ) - 10.0;
    sigma = ( randu() * 10.0 ) + 2.0;
    y = pdf( x, a, b, mu, sigma );
    console.log( 'x: %d, a: %d, b: %d, mu: %d, sigma: %d, f(x;a,b,mu,sigma): %d', x.toFixed( 4 ), a.toFixed( 4 ), b.toFixed( 4 ), mu.toFixed( 4 ), sigma.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">

[cdf]: https://en.wikipedia.org/wiki/Cumulative_distribution_function

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

[normal-distribution]: https://en.wikipedia.org/wiki/Normal_distribution

[truncated-normal-distribution]: https://en.wikipedia.org/wiki/Truncated_normal_distribution

</section>

<!-- /.links -->