Density, distribution function, quantile function and random generation for hurdle distributions.
Usage
dhurdle_poisson(x, lambda, hu, log = FALSE)
phurdle_poisson(q, lambda, hu, lower.tail = TRUE, log.p = FALSE)
qhurdle_poisson(p, lambda, hu, lower.tail = TRUE, log.p = FALSE)
rhurdle_poisson(n, lambda, hu)
dhurdle_negbinomial(x, mu, shape, hu, log = FALSE)
phurdle_negbinomial(q, mu, shape, hu, lower.tail = TRUE, log.p = FALSE)
qhurdle_negbinomial(p, mu, shape, hu, lower.tail = TRUE, log.p = FALSE)
rhurdle_negbinomial(n, mu, shape, hu)
dhurdle_gamma(x, shape, scale, hu, log = FALSE)
phurdle_gamma(q, shape, scale, hu, lower.tail = TRUE, log.p = FALSE)
qhurdle_gamma(p, shape, scale, hu, lower.tail = TRUE, log.p = FALSE)
rhurdle_gamma(n, shape, scale, hu)
dhurdle_lognormal(x, mu, sigma, hu, log = FALSE)
phurdle_lognormal(q, mu, sigma, hu, lower.tail = TRUE, log.p = FALSE)
qhurdle_lognormal(p, mu, sigma, hu, lower.tail = TRUE, log.p = FALSE)
rhurdle_lognormal(n, mu, sigma, hu)Arguments
- x
Vector of quantiles.
- hu
hurdle 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.- p
Vector of probabilities.
- n
Number of draws to sample from the distribution.
- mu, lambda
location parameter
- shape
shape parameter
- sigma, scale
scale parameter