# @stdlib/stats-base-dists-triangular-logpdf

Triangular distribution logarithm of probability density function (PDF).

## Usage no npm install needed!

<script type="module">
import stdlibStatsBaseDistsTriangularLogpdf from 'https://cdn.skypack.dev/@stdlib/stats-base-dists-triangular-logpdf';
</script>

# Logarithm of Probability Density Function

Triangular distribution logarithm of probability density function (PDF).

The probability density function (PDF) for a triangular random variable is

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

## Installation

npm install @stdlib/stats-base-dists-triangular-logpdf


## Usage

var logpdf = require( '@stdlib/stats-base-dists-triangular-logpdf' );


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

Evaluates the natural logarithm of the probability density function (PDF) for a triangular distribution with parameters a (lower limit), b (upper limit) and c (mode).

var y = logpdf( 0.5, -1.0, 1.0, 0.0 );
// returns ~-0.693

y = logpdf( 0.5, -1.0, 1.0, 0.5 );
// returns 0.0

y = logpdf( -10.0, -20.0, 0.0, -2.0 );
// returns ~-2.89

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


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

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

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

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

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


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

var y = logpdf( 1.0, 1.0, 0.0, 1.5 );
// returns NaN

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

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


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

Returns a function for evaluating the natural logarithm of the probability density function (PDF) of a triangular distribution with parameters a (lower limit), b (upper limit) and c (mode).

var mylogpdf = logpdf.factory( 0.0, 10.0, 5.0 );
var y = mylogpdf( 2.0 );
// returns ~-2.526

y = mylogpdf( 12.0 );
// returns -Infinity


## 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.

## Examples

var randu = require( '@stdlib/random-base-randu' );
var logpdf = require( '@stdlib/stats-base-dists-triangular-logpdf' );

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 = logpdf( 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 ) );
}


## Notice

This package is part of 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, see the main project repository.