@stdlib/stats-base-dists-geometric-logpmf
v0.3.1TypeScript
Geometric distribution logarithm of probability mass function (PMF).
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Published by The Stdlib Authors
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About stdlib...
Logarithm of Probability Mass Function
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> [Geometric][geometric-distribution] distribution logarithm of [probability mass function][pmf] (PMF).
The [probability mass function][pmf] (PMF) for a [geometric][geometric-distribution] random variable is defined as
where 0 <= p <= 1 is the success probability. The random variable X denotes the number of failures until the first success in a sequence of independent Bernoulli trials.
Installation
``bash`
npm install @stdlib/stats-base-dists-geometric-logpmf
Usage
`javascript`
var logpmf = require( '@stdlib/stats-base-dists-geometric-logpmf' );
#### logpmf( x, p )
Evaluates the logarithm of the [probability mass function][pmf] (PMF) of a [geometric][geometric-distribution] distribution with success probability 0 <= p <= 1.
`javascript
var y = logpmf( 4.0, 0.3 );
// returns ~-2.631
y = logpmf( 2.0, 0.7 );
// returns ~-2.765
y = logpmf( -1.0, 0.5 );
// returns -Infinity
`
If provided NaN as any argument, the function returns NaN.
`javascript
var y = logpmf( NaN, 0.0 );
// returns NaN
y = logpmf( 0.0, NaN );
// returns NaN
`
If provided a success probability p outside of the interval [0,1], the function returns NaN.
`javascript
var y = logpmf( 2.0, -1.0 );
// returns NaN
y = logpmf( 2.0, 1.5 );
// returns NaN
`
#### logpmf.factory( p )
Returns a function for evaluating the logarithm of the [probability mass function][pmf] (PMF) of a [geometric][geometric-distribution] distribution with success probability 0 <= p <= 1.
`javascript
var mylogpmf = logpmf.factory( 0.5 );
var y = mylogpmf( 3.0 );
// returns ~-2.773
y = mylogpmf( 1.0 );
// returns ~-1.386
`
Notes
- In virtually all cases, using the logpmf or logcdf functions is preferable to manually computing the logarithm of the pmf or cdf, respectively, since the latter is prone to overflow and underflow.
Examples
`javascript
var uniform = require( '@stdlib/random-array-uniform' );
var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var logEachMap = require( '@stdlib/console-log-each-map' );
var logpmf = require( '@stdlib/stats-base-dists-geometric-logpmf' );
var opts = {
'dtype': 'float64'
};
var p = uniform( 10, 0.0, 1.0, opts );
var x = discreteUniform( 10, 0, 5, opts );
logEachMap( 'x: %d, p: %0.4f, ln( P( X = x; p ) ): %0.4f', x, p, logpmf );
`
*
C APIs
$3
`c`
#include "stdlib/stats/base/dists/geometric/logpmf.h"
#### stdlib_base_dists_geometric_logpmf( x, p )
Evaluates the logarithm of the [probability mass function][pmf] (PMF) of the [geometric][geometric-distribution] distribution with success probability 0 <= p <= 1.
`c`
double out = stdlib_base_dists_geometric_logpmf( 4.0, 0.3 );
// returns ~-2.631
The function accepts the following arguments:
- x: [in] double input value.[in] double
- p: probability of success.
`c`
double stdlib_base_dists_geometric_logpmf( const double x, const double p );
$3
`c
#include "stdlib/stats/base/dists/geometric/logpmf.h"
#include "stdlib/math/base/special/round.h"
#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 ) {
double x;
double p;
double y;
int i;
for ( i = 0; i < 25; i++ ) {
x = stdlib_base_round( random_uniform( 0.0, 40.0 ) );
p = random_uniform( 0.0, 1.0 );
y = stdlib_base_dists_geometric_logpmf( x, p );
printf( "x: %lf, p: %lf, ln(P(X=x;p)): %lf\n", x, p, 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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[geometric-distribution]: https://en.wikipedia.org/wiki/Geometric_distribution
[pmf]: https://en.wikipedia.org/wiki/Probability_mass_function