# Kurtosis

Triangular distribution excess kurtosis.

The excess kurtosis for a triangular random variable with lower limit a, upper limit b, and mode c is

## Usage

var kurtosis = require( '@stdlib/math/base/dists/triangular/kurtosis' );


#### kurtosis( a, b, c )

Returns the excess kurtosis of a triangular distribution with minimum support a, maximum supportb, and mode c.

var v = kurtosis( 0.0, 1.0, 0.8 );
// returns -0.6

v = kurtosis( 4.0, 12.0, 5.0 );
// returns -0.6

v = kurtosis( 2.0, 8.0, 5.0 );
// returns -0.6


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

var v = kurtosis( NaN, 4.0, 2.0 );
// returns NaN

v = kurtosis( 0.0, NaN, 2.0 );
// returns NaN

v = kurtosis( 0.0, 4.0, NaN );
// returns NaN


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

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

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

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


## Examples

var randu = require( '@stdlib/random/base/randu' );
var kurtosis = require( '@stdlib/math/base/dists/triangular/kurtosis' );

var a;
var b;
var c;
var v;
var i;

for ( i = 0; i < 10; i++ ) {
a = ( randu()*10.0 );
b = ( randu()*10.0 ) + a;
c = ( randu()*( b-a ) ) + a;
v = kurtosis( a, b, c );
console.log( 'a: %d, b: %d, c: %d, Kurt(X;a,b,c): %d', a.toFixed( 4 ), b.toFixed( 4 ), c.toFixed( 4 ), v.toFixed( 4 ) );
}