Title: | A Faster Implementation of the Poisson-Binomial Distribution |
---|---|
Description: | Provides the probability, distribution, and quantile functions and random number generator for the Poisson-Binomial distribution. This package relies on FFTW to implement the discrete Fourier transform, so that it is much faster than the existing implementation of the same algorithm in R. |
Authors: | Santiago Olivella [aut, cre], Yuki Shiraito [aut, cre] |
Maintainer: | Santiago Olivella <[email protected]> |
License: | GPL (>= 2) |
Version: | 1.0.1 |
Built: | 2024-11-25 06:45:24 UTC |
Source: | CRAN |
Probability mass, distribution, quantile and function, and random number generator for the Poisson-Binomial distribution with parameter vector pp
(the probability parameter of the component Binomial random variables).
dpoisbinom(x, pp, log_d = FALSE) ppoisbinom(q, pp, lower_tail = TRUE, log_p = FALSE) qpoisbinom(p, pp, lower_tail = TRUE, log_p = FALSE) rpoisbinom(n,pp)
dpoisbinom(x, pp, log_d = FALSE) ppoisbinom(q, pp, lower_tail = TRUE, log_p = FALSE) qpoisbinom(p, pp, lower_tail = TRUE, log_p = FALSE) rpoisbinom(n,pp)
x , q
|
vector of quantiles. |
p , pp
|
vector of probabilities. |
n |
number of random deviates. |
log_d , log_p
|
logical; if TRUE, probabilities are given in the log scale. |
lower_tail |
logical; if TRUE (default), probabilities are |
The Poisson-Binomial distribution is the distribution of a sum of independent and not identically distributed Binomial random variables. It is parameterized by the vector of
possibly distinct probability parameters of these Binomial distributions, and is computed using a discrete Fourier transform. See Hong (2013) for details.
dpoisbinom
gives the mass, ppoisbinom
gives the distribution function, qpoisbinom
gives the quantile function and rpoisbinom
generates random deviates.
If pp
contains values outside of [], an error is returned.
The length of the result is determined by n
in rpoisbinom
, and is the length of the first argument for all other functions.
Shiraito, Y. and Olivella, S. (2017).
Hong, Y. (2013) “On computing the distribution function for the Poisson binomial distribution”. Computational Statistics and Data Analysis, 59, 41–51.
## Binomial probabilities pp <- runif(500) ## PMF dpoisbinom(36, pp) ## CDF ppoisbinom(36, pp) ## Quantile function qpoisbinom(0.3, pp) ## Random deviates rpoisbinom(5, pp)
## Binomial probabilities pp <- runif(500) ## PMF dpoisbinom(36, pp) ## CDF ppoisbinom(36, pp) ## Quantile function qpoisbinom(0.3, pp) ## Random deviates rpoisbinom(5, pp)