Poisson {stats}  R Documentation 
Density, distribution function, quantile function and random
generation for the Poisson distribution with parameter lambda
.
dpois(x, lambda, log = FALSE)
ppois(q, lambda, lower.tail = TRUE, log.p = FALSE)
qpois(p, lambda, lower.tail = TRUE, log.p = FALSE)
rpois(n, lambda)
x 
vector of (nonnegative integer) quantiles. 
q 
vector of quantiles. 
p 
vector of probabilities. 
n 
number of random values to return. 
lambda 
vector of (nonnegative) means. 
log , log.p 
logical; if TRUE, probabilities p are given as log(p). 
lower.tail 
logical; if TRUE (default), probabilities are

The Poisson distribution has density
p(x) = \frac{\lambda^x e^{\lambda}}{x!}
for x = 0, 1, 2, \ldots
.
The mean and variance are E(X) = Var(X) = \lambda
.
Note that \lambda = 0
is really a limit case (setting
0^0 = 1
) resulting in a point mass at 0
, see also the example.
If an element of x
is not integer, the result of dpois
is zero, with a warning.
p(x)
is computed using Loader's algorithm, see the reference in
dbinom
.
The quantile is right continuous: qpois(p, lambda)
is the smallest
integer x
such that P(X \le x) \ge p
.
Setting lower.tail = FALSE
allows to get much more precise
results when the default, lower.tail = TRUE
would return 1, see
the example below.
dpois
gives the (log) density,
ppois
gives the (log) distribution function,
qpois
gives the quantile function, and
rpois
generates random deviates.
Invalid lambda
will result in return value NaN
, with a warning.
The length of the result is determined by n
for
rpois
, and is the maximum of the lengths of the
numerical arguments for the other functions.
The numerical arguments other than n
are recycled to the
length of the result. Only the first elements of the logical
arguments are used.
rpois
returns a vector of type integer unless generated
values exceed the maximum representable integer when double
values are returned.
dpois
uses C code contributed by Catherine Loader
(see dbinom
).
ppois
uses pgamma
.
qpois
uses the Cornish–Fisher Expansion to include a skewness
correction to a normal approximation, followed by a search.
rpois
uses
Ahrens, J. H. and Dieter, U. (1982). Computer generation of Poisson deviates from modified normal distributions. ACM Transactions on Mathematical Software, 8, 163–179.
Distributions for other standard distributions, including
dbinom
for the binomial and dnbinom
for
the negative binomial distribution.
require(graphics)
log(dpois(0:7, lambda = 1) * gamma(1+ 0:7)) # == 1
Ni < rpois(50, lambda = 4); table(factor(Ni, 0:max(Ni)))
1  ppois(10*(15:25), lambda = 100) # becomes 0 (cancellation)
ppois(10*(15:25), lambda = 100, lower.tail = FALSE) # no cancellation
par(mfrow = c(2, 1))
x < seq(0.01, 5, 0.01)
plot(x, ppois(x, 1), type = "s", ylab = "F(x)", main = "Poisson(1) CDF")
plot(x, pbinom(x, 100, 0.01), type = "s", ylab = "F(x)",
main = "Binomial(100, 0.01) CDF")
## The (limit) case lambda = 0 :
stopifnot(identical(dpois(0,0), 1),
identical(ppois(0,0), 1),
identical(qpois(1,0), 0))