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README.md |
Probability Mass Function
Poisson distribution probability mass function (PMF).
The probability mass function (PMF) for a Poisson random variable is
where lambda > 0
is the mean parameter.
Usage
var pmf = require( '@stdlib/stats/base/dists/poisson/pmf' );
pmf( x, lambda )
Evaluates the probability mass function (PMF) of a Poisson distribution with mean parameter lambda
.
var y = pmf( 4.0, 3.0 );
// returns ~0.168
y = pmf( 1.0, 3.0 );
// returns ~0.149
y = pmf( -1.0, 2.0 );
// returns 0.0
If provided NaN
as any argument, the function returns NaN
.
var y = pmf( NaN, 2.0 );
// returns NaN
y = pmf( 0.0, NaN );
// returns NaN
If provided a negative mean parameter lambda
, the function returns NaN
.
var y = pmf( 2.0, -1.0 );
// returns NaN
y = pmf( 4.0, -2.0 );
// returns NaN
If provided lambda = 0
, the function evaluates the PMF of a degenerate distribution centered at 0.0
.
var y = pmf( 2.0, 0.0 );
// returns 0.0
y = pmf( 0.0, 0.0 );
// returns 1.0
pmf.factory( lambda )
Returns a function for evaluating the probability mass function (PMF) of a Poisson distribution with mean parameter lambda
.
var mypmf = pmf.factory( 1.0 );
var y = mypmf( 3.0 );
// returns ~0.061
y = mypmf( 1.0 );
// returns ~0.368
Examples
var randu = require( '@stdlib/random/base/randu' );
var round = require( '@stdlib/math/base/special/round' );
var pmf = require( '@stdlib/stats/base/dists/poisson/pmf' );
var lambda;
var x;
var y;
var i;
for ( i = 0; i < 10; i++ ) {
x = round( randu() * 10.0 );
lambda = randu() * 10.0;
y = pmf( x, lambda );
console.log( 'x: %d, λ: %d, P(X=x;λ): %d', x, lambda.toFixed( 4 ), y.toFixed( 4 ) );
}