dhpois {distributions3} | R Documentation |
Density, distribution function, quantile function, and random
generation for the zero-hurdle Poisson distribution with
parameters lambda
and pi
.
dhpois(x, lambda, pi, log = FALSE)
phpois(q, lambda, pi, lower.tail = TRUE, log.p = FALSE)
qhpois(p, lambda, pi, lower.tail = TRUE, log.p = FALSE)
rhpois(n, lambda, pi)
x |
vector of (non-negative integer) quantiles. |
lambda |
vector of (non-negative) Poisson parameters. |
pi |
vector of zero-hurdle probabilities in the unit interval. |
log, log.p |
logical indicating whether probabilities p are given as log(p). |
q |
vector of quantiles. |
lower.tail |
logical indicating whether probabilities are |
p |
vector of probabilities. |
n |
number of random values to return. |
All functions follow the usual conventions of d/p/q/r functions
in base R. In particular, all four hpois
functions for the
hurdle Poisson distribution call the corresponding pois
functions for the Poisson distribution from base R internally.
Note, however, that the precision of qhpois
for very large
probabilities (close to 1) is limited because the probabilities
are internally handled in levels and not in logs (even if log.p = TRUE
).
## theoretical probabilities for a hurdle Poisson distribution
x <- 0:8
p <- dhpois(x, lambda = 2.5, pi = 0.75)
plot(x, p, type = "h", lwd = 2)
## corresponding empirical frequencies from a simulated sample
set.seed(0)
y <- rhpois(500, lambda = 2.5, pi = 0.75)
hist(y, breaks = -1:max(y) + 0.5)