@stdlib/stats-base-dists-discrete-uniform-logpmf

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Logarithm of Probability Mass Function

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

where a is the minimum support and b is the maximum support of the distribution. The parameters must satisfy a <= b.

Installation

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

Usage

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

logpmf( x, a, b )

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

logpmf.factory( a, b )

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

Examples

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, a, b, y.toFixed( 4 ) );
}

C APIs

Usage

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

stdlib_base_dists_discrete_uniform_logpmf( x, a, b )

Evaluates the natural logarithm of the probability mass function (PMF) for a discrete uniform distribution with parameters a (minimum support) and b (maximum support).

double out = stdlib_base_dists_discrete_uniform_logpmf( 2.0, 0, 4 );
// returns ~-1.609

The function accepts the following arguments:

• x: [in] double input value.
• a: [in] int32_t minimum support.
• b: [in] int32_t maximum support.

double stdlib_base_dists_discrete_uniform_logpmf( const double x, const int32_t a, const int32_t b );

Examples

#include "stdlib/stats/base/dists/discrete-uniform/logpmf.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 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( a*1.0, b*1.0 ) );
        y = stdlib_base_dists_discrete_uniform_logpmf( x, a, b );
        printf( "x:%lf, a: %d, b: %d, ln(P(X=x;a,b)): %lf\n", x, a, b, y );
    }
}

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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

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License

See LICENSE.

Copyright

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