Density and distribution functions for zero-inflated distributions.

dzero_inflated_poisson(x, lambda, zi, log = FALSE)

pzero_inflated_poisson(q, lambda, zi, lower.tail = TRUE, log.p = FALSE)

dzero_inflated_negbinomial(x, mu, shape, zi, log = FALSE)

pzero_inflated_negbinomial(q, mu, shape, zi, lower.tail = TRUE, log.p = FALSE)

dzero_inflated_binomial(x, size, prob, zi, log = FALSE)

pzero_inflated_binomial(q, size, prob, zi, lower.tail = TRUE, log.p = FALSE)

dzero_inflated_beta_binomial(x, size, mu, phi, zi, log = FALSE)

pzero_inflated_beta_binomial(
q,
size,
mu,
phi,
zi,
lower.tail = TRUE,
log.p = FALSE
)

dzero_inflated_beta(x, shape1, shape2, zi, log = FALSE)

pzero_inflated_beta(q, shape1, shape2, zi, lower.tail = TRUE, log.p = FALSE)

## Arguments

x

Vector of quantiles.

zi

zero-inflation probability

log

Logical; If TRUE, values are returned on the log scale.

q

Vector of quantiles.

lower.tail

Logical; If TRUE (default), return P(X <= x). Else, return P(X > x) .

log.p

Logical; If TRUE, values are returned on the log scale.

mu, lambda

location parameter

shape, shape1, shape2

shape parameter

size

number of trials

prob

probability of success on each trial

phi

precision parameter

## Details

The density of a zero-inflated distribution can be specified as follows. If $$x = 0$$ set $$f(x) = \theta + (1 - \theta) * g(0)$$. Else set $$f(x) = (1 - \theta) * g(x)$$, where $$g(x)$$ is the density of the non-zero-inflated part.