@stdlib/stats/base/dists/triangular/logcdf/README.md

Standard library statistical functions.

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# Logarithm of Cumulative Distribution Function

> [Triangular][triangular-distribution] distribution logarithm of [cumulative distribution function][cdf].

<section class="intro">

The [cumulative distribution function][cdf] for a [triangular][triangular-distribution] random variable is

<!-- <equation class="equation" label="eq:triangular_cdf" align="center" raw="F(x;a,b,c) = \begin{cases} 0 & \text{for } x \leq a \\ \frac{(x-a)^2}{(b-a)(c-a)} & \text{for } a < x \leq c \\ 1-\frac{(b-x)^2}{(b-a)(b-c)} & \text{for } c < x < b \\ 1 & \text{for } b \leq x \end{cases}" alt="Cumulative distribution function for a Triangular distribution."> -->

<div class="equation" align="center" data-raw-text="F(x;a,b,c) = \begin{cases} 0 &amp; \text{for } x \leq a \\ \frac{(x-a)^2}{(b-a)(c-a)} &amp; \text{for } a &lt; x \leq c \\ 1-\frac{(b-x)^2}{(b-a)(b-c)} &amp; \text{for } c &lt; x &lt; b \\ 1 &amp; \text{for } b \leq x \end{cases}" data-equation="eq:triangular_cdf">
    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@51534079fef45e990850102147e8945fb023d1d0/lib/node_modules/@stdlib/stats/base/dists/triangular/logcdf/docs/img/equation_triangular_cdf.svg" alt="Cumulative distribution function for a Triangular distribution.">
    <br>
</div>

<!-- </equation> -->

where `a` is the lower limit, `b` is the upper limit, and `c` is the mode.

</section>

<!-- /.intro -->

<section class="usage">

## Usage

```javascript
var logcdf = require( '@stdlib/stats/base/dists/triangular/logcdf' );
```

#### logcdf( x, a, b, c )

Evaluates the natural logarithm of the [cumulative distribution function][cdf] (CDF) for a [triangular][triangular-distribution] distribution with parameters `a` (lower limit), `b` (upper limit) and `c` (mode).

```javascript
var y = logcdf( 0.5, -1.0, 1.0, 0.0 );
// returns ~-0.134

y = logcdf( 0.5, -1.0, 1.0, 0.5 );
// returns ~-0.288

y = logcdf( -10.0, -20.0, 0.0, -2.0 );
// returns ~-1.281

y = logcdf( -2.0, -1.0, 1.0, 0.0 );
// returns -Infinity
```

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

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

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

y = logcdf( 0.0, 0.0, NaN, 0.5 );
// returns NaN

y = logcdf( 2.0, 1.0, 0.0, NaN );
// returns NaN
```

If provided parameters not satisfying `a <= c <= b`, the function returns `NaN`.

```javascript
var y = logcdf( 2.0, 1.0, 0.0, 1.5 );
// returns NaN

y = logcdf( 2.0, 1.0, 0.0, -1.0 );
// returns NaN

y = logcdf( 2.0, 0.0, -1.0, 0.5 );
// returns NaN
```

#### logcdf.factory( a, b, c )

Returns a function for evaluating the natural logarithm of the [cumulative distribution function][cdf] of a [triangular][triangular-distribution] distribution with parameters `a` (lower limit), `b` (upper limit) and `c` (mode).

```javascript
var mylogcdf = logcdf.factory( 0.0, 10.0, 2.0 );
var y = mylogcdf( 0.5 );
// returns ~-4.382

y = mylogcdf( 8.0 );
// returns ~-0.051
```

</section>

<!-- /.usage -->

<section class="notes">

## Notes

-   In virtually all cases, using the `logpdf` or `logcdf` functions is preferable to manually computing the logarithm of the `pdf` or `cdf`, respectively, since the latter is prone to overflow and underflow.

</section>

<!-- /.notes -->

<section class="examples">

## Examples

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

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

var a;
var b;
var c;
var x;
var y;
var i;

for ( i = 0; i < 25; i++ ) {
    x = randu() * 30.0;
    a = randu() * 10.0;
    b = a + (randu() * 40.0);
    c = a + ((b-a) * randu());
    y = logcdf( x, a, b, c );
    console.log( 'x: %d, a: %d, b: %d, c: %d, ln(F(x;a,b,c)): %d', x.toFixed( 4 ), a.toFixed( 4 ), b.toFixed( 4 ), c.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>

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<section class="links">

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

[triangular-distribution]: https://en.wikipedia.org/wiki/Triangular_distribution

</section>

<!-- /.links -->