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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.
import pmf from 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-dists-negative-binomial-pmf@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-negative-binomial-pmf@esm/index.mjs';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 ~0.349While 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 ~0.051If 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 NaNIf 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 NaNIf 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 NaNReturns 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<!DOCTYPE html> <html lang="en"> <body> <script type="module"> import uniform from 'https://cdn.jsdelivr.net/gh/stdlib-js/random-array-uniform@esm/index.mjs'; import discreteUniform from 'https://cdn.jsdelivr.net/gh/stdlib-js/random-array-discrete-uniform@esm/index.mjs'; import logEachMap from 'https://cdn.jsdelivr.net/gh/stdlib-js/console-log-each-map@esm/index.mjs'; import pmf from 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-dists-negative-binomial-pmf@esm/index.mjs'; var opts = { 'dtype': 'float64' }; var x = discreteUniform( 10, 0, 30, opts ); var r = uniform( 10, 0.0, 50.0, opts ); var p = uniform( 10, 0.0, 1.0, opts ); logEachMap( 'x: %d, r: %0.4f, p: %0.4f, P(X=x;r,p): %0.4f', x, r, p, pmf ); </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.
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