Natural logarithm of the probability mass function (PMF) for a discrete uniform distribution.
APACHE-2.0 License
Evaluate the natural logarithm of the probability mass function (PMF) for a discrete uniform distribution.
The probability mass function (PMF) for a discrete uniform random variable is
P(X=x;a,b)=\begin{cases} \frac{1}{b - a + 1} & \text{for } x \in \{ a, \ldots, b \} \\ 0 & \text{otherwise} \end{cases}
where a
is the minimum support and b
is the maximum support of the distribution. The parameters must satisfy a <= b
.
npm install @stdlib/stats-base-dists-discrete-uniform-logpmf
Alternatively,
script
tag without installation and bundlers, use the ES Module available on the esm
branch (see README).deno
branch (see README for usage intructions).umd
branch (see README).The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.
To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.
var logpmf = require( '@stdlib/stats-base-dists-discrete-uniform-logpmf' );
Evaluates the natural logarithm of the probability mass function (PMF) for a discrete uniform distribution with parameters a
(minimum support) and b
(maximum support).
var y = logpmf( 2.0, 0, 4 );
// returns ~-1.609
y = logpmf( 5.0, 0, 4 );
// returns -Infinity
y = logpmf( 3, -4, 4 );
// returns ~-2.197
If provided NaN
as any argument, the function returns NaN
.
var y = logpmf( NaN, -2, 2 );
// returns NaN
y = logpmf( 1.0, NaN, 4 );
// returns NaN
y = logpmf( 2.0, 0, NaN );
// returns NaN
If a
or b
is not an integer value, the function returns NaN
.
var y = logpmf( 2.0, 1, 5.5 );
// returns NaN
If provided a > b
, the function returns NaN
.
var y = logpmf( 2.0, 3, 2 );
// returns NaN
Returns a function
for evaluating the PMF for a discrete uniform distribution with parameters a
(minimum support) and b
(maximum support).
var myLogPMF = logpmf.factory( 6, 7 );
var y = myLogPMF( 7.0 );
// returns ~-0.693
y = myLogPMF( 5.0 );
// returns -Infinity
var randint = require( '@stdlib/random-base-discrete-uniform' );
var logpmf = require( '@stdlib/stats-base-dists-discrete-uniform-logpmf' );
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 = logpmf( x, a, b );
console.log( 'x: %d, a: %d, b: %d, ln(P(X=x;a,b)): %d', x.toFixed( 4 ), a.toFixed( 4 ), b.toFixed( 4 ), y.toFixed( 4 ) );
}
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.
Copyright © 2016-2024. The Stdlib Authors.