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README.md |
Kurtosis
Beta prime distribution excess kurtosis.
The excess kurtosis for a beta prime random variable with first shape parameter α
and second shape parameter β
is
when α > 0
and β > 4
. Otherwise, the excess kurtosis is not defined.
Usage
var kurtosis = require( '@stdlib/stats/base/dists/betaprime/kurtosis' );
kurtosis( alpha, beta )
Returns the excess kurtosis of a beta prime distribution with parameters alpha
(first shape parameter) and beta
(second shape parameter).
var v = kurtosis( 2.0, 5.0 );
// returns 54.0
v = kurtosis( 4.0, 12.0 );
// returns ~5.764
v = kurtosis( 12.0, 6.0 );
// returns ~19.49
If provided NaN
as any argument, the function returns NaN
.
var v = kurtosis( NaN, 5.0 );
// returns NaN
v = kurtosis( 2.0, NaN );
// returns NaN
If provided alpha <= 0
, the function returns NaN
.
var v = kurtosis( 0.0, 5.0 );
// returns NaN
v = kurtosis( -1.0, 5.0 );
// returns NaN
If provided beta <= 4
, the function returns NaN
.
var v = kurtosis( 1.0, 3.5 );
// returns NaN
v = kurtosis( 1.0, 2.0 );
// returns NaN
v = kurtosis( 1.0, -1.0 );
// returns NaN
Examples
var randu = require( '@stdlib/random/base/randu' );
var EPS = require( '@stdlib/constants/float64/eps' );
var kurtosis = require( '@stdlib/stats/base/dists/betaprime/kurtosis' );
var alpha;
var beta;
var v;
var i;
for ( i = 0; i < 10; i++ ) {
alpha = ( randu()*10.0 ) + EPS;
beta = ( randu()*10.0 ) + 4.0 + EPS;
v = kurtosis( alpha, beta );
console.log( 'α: %d, β: %d, Kurt(X;α,β): %d', alpha.toFixed( 4 ), beta.toFixed( 4 ), v.toFixed( 4 ) );
}