Quantile Function

Discrete uniform distribution quantile function.

The quantile function for a discrete uniform random variable is

for 0 <= p <= 1, where a is the minimum support and b is the maximum support. The parameters must satisfy a <= b.

Installation

npm install @stdlib/stats-base-dists-discrete-uniform-quantile

Usage

var quantile = require( '@stdlib/stats-base-dists-discrete-uniform-quantile' );

quantile( p, a, b )

Evaluates the quantile function for a discrete uniform distribution with parameters a (minimum support) and b (maximum support).

var y = quantile( 0.8, 0, 1 );
// returns 1

y = quantile( 0.5, 0, 10 );
// returns 5

If provided a probability p outside the interval [0,1], the function returns NaN.

var y = quantile( 1.9, 0, 2 );
// returns NaN

y = quantile( -0.1, 0, 2 );
// returns NaN

If a or b is not an integer value, the function returns NaN.

var y = quantile( 0.2, 1, 5.5 );
// returns NaN

If provided a > b, the function returns NaN.

var y = quantile( 0.4, 2, 1 );
// returns NaN

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

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

y = quantile( 0.0, NaN, 1.0 );
// returns NaN

y = quantile( 0.0, 0.0, NaN );
// returns NaN

quantile.factory( a, b )

Returns a function for evaluating the quantile function of a discrete uniform distribution with parameters a (minimum support) and b (maximum support).

var myquantile = quantile.factory( 0, 4 );
var y = myquantile( 0.8 );
// returns 4

y = myquantile( 0.3 );
// returns 1

Examples

var uniform = require( '@stdlib/random-array-uniform' );
var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var quantile = require( '@stdlib/stats-base-dists-discrete-uniform-quantile' );

var p = uniform( 10, 0.0, 1.0 );
var a = discreteUniform( 10, 0, 5 );
var b = discreteUniform( 10, 2, 8 );

var v;
var i;
for ( i = 0; i < 10; i++ ) {
    v = quantile( p[ i ], a[ i ], b[ i ] );
    console.log( 'p: %d, a: %d, b: %d, Q(p;a,b): %d', p[ i ].toFixed( 4 ), a[ i ], b[ i ], v );
}

C APIs

Usage

#include "stdlib/stats/base/dists/discrete-uniform/quantile.h"

stdlib_base_dists_discrete_uniform_quantile( x, a, b )

Evaluates the quantile function for a discrete uniform distribution with parameters a (minimum support) and b (maximum support).

double out = stdlib_base_dists_discrete_uniform_quantile( 0.8, 0, 1 );
// returns 1.0

The function accepts the following arguments:

• p: [in] double input probability.
• a: [in] int32_t minimum support.
• b: [in] int32_t maximum support.

double stdlib_base_dists_discrete_uniform_quantile( const double p, const int32_t a, const int32_t b );

Examples

#include "stdlib/stats/base/dists/discrete-uniform/quantile.h"
#include "stdlib/math/base/special/round.h"
#include <stdint.h>
#include <stdlib.h>
#include <stdio.h>

static double random_uniform( const double min, const double max ) {
    double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
    return min + ( v*(max-min) );
}

int main( void ) {
    int32_t a;
    int32_t b;
    double p;
    double y;
    int i;

    for ( i = 0; i < 10; i++ ) {
        p = random_uniform( 0.0, 1.0 );
        a = stdlib_base_round( random_uniform( 0.0, 5.0 ) );
        b = stdlib_base_round( random_uniform( a, a + 5.0 ) );
        y = stdlib_base_dists_discrete_uniform_quantile( p, a, b );
        printf( "p: %lf, a: %d, b: %d, Q(p;a,b): %lf\n", p, a, b, y );
    }
}

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.

Community

License

See LICENSE.

Copyright

Copyright © 2016-2026. The Stdlib Authors.