PoissonMix: Mixture of Poisson distributions

In extraDistr: Additional Univariate and Multivariate Distributions

Description

Density, distribution function and random generation for the mixture of Poisson distributions.

Usage

dmixpois(x, lambda, alpha, log = FALSE)

pmixpois(q, lambda, alpha, lower.tail = TRUE, log.p = FALSE)

rmixpois(n, lambda, alpha)

Arguments

x, q	vector of quantiles.
lambda	matrix (or vector) of (non-negative) means.
alpha	matrix (or vector) of mixing proportions; mixing proportions need to sum up to 1.
log, log.p	logical; if TRUE, probabilities p are given as log(p).
lower.tail	logical; if TRUE (default), probabilities are P[X ≤ x] otherwise, P[X > x].
n	number of observations. If length(n) > 1, the length is taken to be the number required.
p	vector of probabilities.

Details

Probability density function

f(x) = α[1] * f1(x; λ[1]) + … + α[k] * fk(x; λ[k])

Cumulative distribution function

F(x) = α[1] * F1(x; λ[1]) + … + α[k] * Fk(x; λ[k])

where sum(α[i]) == 1.

Examples

x <- rmixpois(1e5, c(5, 12, 19), c(1/3, 1/3, 1/3))
xx <- seq(-1, 50)
plot(prop.table(table(x)))
lines(xx, dmixpois(xx, c(5, 12, 19), c(1/3, 1/3, 1/3)), col = "red")
hist(pmixpois(x, c(5, 12, 19), c(1/3, 1/3, 1/3)))

xx <- seq(0, 50, by = 0.01)
plot(ecdf(x))
lines(xx, pmixpois(xx, c(5, 12, 19), c(1/3, 1/3, 1/3)), col = "red", lwd = 2)

extraDistr documentation built on Sept. 7, 2020, 5:09 p.m.