|
||
---|---|---|
.. | ||
docs | ||
lib | ||
package.json | ||
README.md |
Probability Mass Function
Negative binomial distribution probability mass function (PMF).
The probability mass function (PMF) for a negative binomial random variable X
is
where r > 0
is the number of successes until experiment is stopped and 0 < p <= 1
is the success probability. The random variable X
denotes the number of failures until the r
success is reached.
Usage
var pmf = require( '@stdlib/stats/base/dists/negative-binomial/pmf' );
pmf( x, r, p )
Evaluates the probability mass function for a negative binomial distribution with number of successes until experiment is stopped r
and success probability p
.
var y = pmf( 5.0, 20.0, 0.8 );
// returns ~0.157
y = pmf( 21.0, 20.0, 0.5 );
// returns ~0.06
y = pmf( 5.0, 10.0, 0.4 );
// returns ~0.016
y = pmf( 0.0, 10.0, 0.9 );
// returns ~0.349
While r
can be interpreted as the number of successes until the experiment is stopped, the negative binomial distribution is also defined for non-integers r
. In this case, r
denotes shape parameter of the gamma mixing distribution.
var y = pmf( 21.0, 15.5, 0.5 );
// returns ~0.037
y = pmf( 5.0, 7.4, 0.4 );
// returns ~0.051
If provided a r
which is not a positive number, the function returns NaN
.
var y = pmf( 2.0, 0.0, 0.5 );
// returns NaN
y = pmf( 2.0, -2.0, 0.5 );
// returns NaN
If provided NaN
as any argument, the function returns NaN
.
var y = pmf( NaN, 20.0, 0.5 );
// returns NaN
y = pmf( 0.0, NaN, 0.5 );
// returns NaN
y = pmf( 0.0, 20.0, NaN );
// returns NaN
If provided a success probability p
outside of [0,1]
, the function returns NaN
.
var y = pmf( 2.0, 20, -1.0 );
// returns NaN
y = pmf( 2.0, 20, 1.5 );
// returns NaN
pmf.factory( r, p )
Returns a function for evaluating the probability mass function (PMF) of a negative binomial distribution with number of successes until experiment is stopped r
and success probability p
.
var mypmf = pmf.factory( 10, 0.5 );
var y = mypmf( 3.0 );
// returns ~0.03
y = mypmf( 10.0 );
// returns ~0.088
Examples
var randu = require( '@stdlib/random/base/randu' );
var round = require( '@stdlib/math/base/special/round' );
var pmf = require( '@stdlib/stats/base/dists/negative-binomial/pmf' );
var i;
var r;
var p;
var x;
var y;
for ( i = 0; i < 10; i++ ) {
x = round( randu() * 30 );
r = randu() * 50;
p = randu();
y = pmf( x, r, p );
console.log( 'x: %d, r: %d, p: %d, P(X=x;r,p): %d', x, r, p.toFixed( 4 ), y.toFixed( 4 ) );
}