PoissonBinomial-package: Efficient Exact and Approximate Implementations for Computing...

In PoissonBinomial: Efficient Computation of Ordinary and Generalized Poisson Binomial Distributions

Efficient Exact and Approximate Implementations for Computing Ordinary and Generalized Poisson Binomial Distributions

Description

This package implements various algorithms for computing the probability mass function, the cumulative distribution function, quantiles and random numbers of both ordinary and generalized Poisson binomial distributions.

References

Hong, Y. (2013). On computing the distribution function for the Poisson binomial distribution. Computational Statistics & Data Analysis, 59, pp. 41-51. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.csda.2012.10.006")}

Biscarri, W., Zhao, S. D. and Brunner, R. J. (2018) A simple and fast method for computing the Poisson binomial distribution. Computational Statistics and Data Analysis, 31, pp. 216–222. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.csda.2018.01.007")}

Zhang, M., Hong, Y. and Balakrishnan, N. (2018). The generalized Poisson-binomial distribution and the computation of its distribution function. Journal of Statistical Computational and Simulation, 88(8), pp. 1515-1527. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/00949655.2018.1440294")}

Examples

# Functions for ordinary Poisson binomial distributions
set.seed(1)
pp <- c(1, 0, runif(10), 1, 0, 1)
qq <- seq(0, 1, 0.01)

dpbinom(NULL, pp)
ppbinom(7:10, pp, method = "DivideFFT")
qpbinom(qq, pp, method = "Convolve")
rpbinom(10, pp, method = "RefinedNormal")

# Functions for generalized Poisson binomial distributions
va <- rep(5, length(pp))
vb <- 1:length(pp)

dgpbinom(NULL, pp, va, vb, method = "Convolve")
pgpbinom(80:100, pp, va, vb, method = "Convolve")
qgpbinom(qq, pp, va, vb, method = "Convolve")
rgpbinom(100, pp, va, vb, method = "Convolve")

PoissonBinomial documentation built on May 29, 2024, 8:55 a.m.