Quantile Function
Beta distribution quantile function.
The quantile function for a beta random variable is
for 0 <= p <= 1
, where alpha > 0
is the first shape parameter and beta > 0
is the second shape parameter and F(x;alpha,beta)
denotes the cumulative distribution function of a beta random variable with parameters alpha
and beta
.
Usage
var quantile = require( '@stdlib/stats/base/dists/beta/quantile' );
quantile( p, alpha, beta )
Evaluates the quantile function for a beta distribution with parameters alpha
(first shape parameter) and beta
(second shape parameter).
var y = quantile( 0.8, 2.0, 1.0 );
// returns ~0.894
y = quantile( 0.5, 4.0, 2.0 );
// returns ~0.686
If provided a probability p
outside the interval [0,1]
, the function returns NaN
.
var y = quantile( 1.9, 1.0, 1.0 );
// returns NaN
y = quantile( -0.1, 1.0, 1.0 );
// returns NaN
If provided NaN
as any argument, the function returns NaN
.
var y = quantile( NaN, 1.0, 1.0 );
// returns NaN
y = quantile( 0.5, NaN, 1.0 );
// returns NaN
y = quantile( 0.5, 1.0, NaN );
// returns NaN
If provided alpha <= 0
, the function returns NaN
.
var y = quantile( 0.4, -1.0, 1.0 );
// returns NaN
y = quantile( 0.4, 0.0, 1.0 );
// returns NaN
If provided beta <= 0
, the function returns NaN
.
var y = quantile( 0.4, 1.0, -1.0 );
// returns NaN
y = quantile( 0.4, 1.0, 0.0 );
// returns NaN
quantile.factory( alpha, beta )
Returns a function for evaluating the quantile function of a beta distribution with parameters alpha
(first shape parameter) and beta
(second shape parameter).
var myquantile = quantile.factory( 2.0, 2.0 );
var y = myquantile( 0.8 );
// returns ~0.713
y = myquantile( 0.4 );
// returns ~0.433
Examples
var randu = require( '@stdlib/random/base/randu' );
var EPS = require( '@stdlib/constants/float64/eps' );
var quantile = require( '@stdlib/stats/base/dists/beta/quantile' );
var alpha;
var beta;
var p;
var y;
var i;
for ( i = 0; i < 10; i++ ) {
p = randu();
alpha = ( randu()*5.0 ) + EPS;
beta = ( randu()*5.0 ) + EPS;
y = quantile( p, alpha, beta );
console.log( 'p: %d, α: %d, β: %d, Q(p;α,β): %d', p.toFixed( 4 ), alpha.toFixed( 4 ), beta.toFixed( 4 ), y.toFixed( 4 ) );
}