@stdlib/stats-base-dists-discrete-uniform-pmf
v0.3.2TypeScript
Discrete uniform distribution probability mass function (PMF).
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Published by The Stdlib Authors
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About stdlib...
Probability Mass Function
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> [Discrete uniform][discrete-uniform-distribution] distribution [probability mass function][pmf] (PMF).
The [probability mass function][pmf] (PMF) for a [discrete uniform][discrete-uniform-distribution] random variable is
where a is the minimum support and b is the maximum support of the distribution. The parameters must satisfy a <= b.
Installation
``bash`
npm install @stdlib/stats-base-dists-discrete-uniform-pmf
Usage
`javascript`
var pmf = require( '@stdlib/stats-base-dists-discrete-uniform-pmf' );
#### pmf( x, a, b )
Evaluates the [probability mass function][pmf] (PMF) for a [discrete uniform][discrete-uniform-distribution] distribution with parameters a (minimum support) and b (maximum support).
`javascript
var y = pmf( 2.0, 0, 4 );
// returns ~0.2
y = pmf( 5.0, 0, 4 );
// returns 0.0
y = pmf( 3, -4, 4 );
// returns ~0.111
`
If provided NaN as any argument, the function returns NaN.
`javascript
var y = pmf( NaN, -2, 2 );
// returns NaN
y = pmf( 1.0, NaN, 4 );
// returns NaN
y = pmf( 2.0, 0, NaN );
// returns NaN
`
If a or b is not an integer value, the function returns NaN.
`javascript`
var y = pmf( 2.0, 1, 5.5 );
// returns NaN
If provided a > b, the function returns NaN.
`javascript`
var y = pmf( 2.0, 3, 2 );
// returns NaN
#### pmf.factory( a, b )
Returns a function for evaluating the [PMF][pmf] for a [discrete uniform][discrete-uniform-distribution] distribution with parameters a (minimum support) and b (maximum support).
`javascript
var myPDF = pmf.factory( 6, 7 );
var y = myPDF( 7.0 );
// returns 0.5
y = myPDF( 5.0 );
// returns 0.0
`
Examples
`javascript
var randint = require( '@stdlib/random-base-discrete-uniform' );
var pmf = require( '@stdlib/stats-base-dists-discrete-uniform-pmf' );
var randa = randint.factory( 0, 10 );
var randb = randint.factory();
var a;
var b;
var x;
var y;
var i;
for ( i = 0; i < 25; i++ ) {
a = randa();
x = randb( a, a+randa() );
b = randb( a, a+randa() );
y = pmf( x, a, b );
console.log( 'x: %d, a: %d, b: %d, P(X=x;a,b): %d', x, a, b, y.toFixed( 4 ) );
}
`
C APIs
$3
`c`
#include "stdlib/stats/base/dists/discrete-uniform/pmf.h"
#### stdlib_base_dists_discrete_uniform_pmf( x, a, b )
Evaluates the [probability mass function][pmf] (PMF) for a [discrete uniform][discrete-uniform-distribution] distribution with parameters a (minimum support) and b (maximum support).
`c`
double out = stdlib_base_dists_discrete_uniform_pmf( 2.0, 0, 4 );
// returns ~0.2
The function accepts the following arguments:
- x: [in] double input value.[in] int32_t
- a: minimum support.[in] int32_t
- b: maximum support.
`c`
double stdlib_base_dists_discrete_uniform_pmf( const double x, const int32_t a, const int32_t b );
$3
`c
#include "stdlib/stats/base/dists/discrete-uniform/pmf.h"
#include "stdlib/math/base/special/round.h"
#include
#include
#include
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 x;
double y;
int i;
for ( i = 0; i < 10; i++ ) {
a = stdlib_base_round( random_uniform( 0.0, 10.0 ) );
b = stdlib_base_round( random_uniform( a, a+10.0 ) );
x = stdlib_base_round( random_uniform( a1.0, b1.0 ) );
y = stdlib_base_dists_discrete_uniform_logpmf( x, a, b );
printf( "x:%lf, a: %d, b: %d, P(X=x;a,b): %lf\n", x, a, b, y );
}
}
`
*
Notice
This package is part of [stdlib][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][stdlib], see the main project [repository][stdlib].
#### Community
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---
License
See [LICENSE][stdlib-license].
Copyright
Copyright © 2016-2026. The Stdlib [Authors][stdlib-authors].
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[pmf]: https://en.wikipedia.org/wiki/Probability_mass_function
[discrete-uniform-distribution]: https://en.wikipedia.org/wiki/Discrete_uniform_distribution