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Geometric distribution logarithm of probability mass function (PMF).
The probability mass function (PMF) for a geometric 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.
import logpmf from 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-dists-geometric-logpmf@esm/index.mjs';
You can also import the following named exports from the package:
import { factory } from 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-dists-geometric-logpmf@esm/index.mjs';
Evaluates the logarithm of the probability mass function (PMF) of a geometric distribution with success probability 0 <= p <= 1
.
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
.
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
.
var y = logpmf( 2.0, -1.0 );
// returns NaN
y = logpmf( 2.0, 1.5 );
// returns NaN
Returns a function for evaluating the logarithm of the probability mass function (PMF) of a geometric distribution with success probability 0 <= p <= 1
.
var mylogpmf = logpmf.factory( 0.5 );
var y = mylogpmf( 3.0 );
// returns ~-2.773
y = mylogpmf( 1.0 );
// returns ~-1.386
- In virtually all cases, using the
logpmf
orlogcdf
functions is preferable to manually computing the logarithm of thepmf
orcdf
, respectively, since the latter is prone to overflow and underflow.
<!DOCTYPE html>
<html lang="en">
<body>
<script type="module">
import randu from 'https://cdn.jsdelivr.net/gh/stdlib-js/random-base-randu@esm/index.mjs';
import round from 'https://cdn.jsdelivr.net/gh/stdlib-js/math-base-special-round@esm/index.mjs';
import logpmf from 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-dists-geometric-logpmf@esm/index.mjs';
var p;
var x;
var y;
var i;
for ( i = 0; i < 10; i++ ) {
x = round( randu() * 5.0 );
p = randu();
y = logpmf( x, p );
console.log( 'x: %d, p: %d, ln( P( X = x; p ) ): %d', x, p.toFixed( 4 ), y.toFixed( 4 ) );
}
</script>
</body>
</html>
This package is part of stdlib, a standard library 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.
See LICENSE.
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