Poisson Distribution

DESCRIPTION:

Functions for the density, cumulative distribution, quantiles and random generation of the Poisson distribution.

USAGE:

dpois(x, lambda, log=F) 
ppois(q, lambda) 
qpois(p, lambda) 
rpois(n, lambda, bigdata=F) 

REQUIRED ARGUMENTS:

x
vector or bdVector of (positive) quantiles. Missing values ( NAs) are allowed.
q
vector or bdVector of (positive) quantiles. Missing values ( NAs) are allowed.
p
vector or bdVector of probabilities. Missing values ( NAs) are allowed.
n
sample size. If length(n) is larger than 1, then length(n) random values are returned.
lambda
vector or bdVector of (positive) means.

OPTIONAL ARGUMENTS:

bigdata
a logical value; if TRUE, an object of type bdVector is returned. Otherwise, a vector object is returned. This argument can be used only if the bigdata library section has been loaded.
log
a logical scalar; if TRUE, dpois will return the log of the density, not the density itself.

VALUE:

density ( dpois), probability ( ppois), quantile ( qpois), or random sample ( rpois) for the Poisson distribution with mean lambda. The quantile is defined as the smallest value q such that Pr(Poisson random variate <= x) >= p.

SIDE EFFECTS:

rpois causes the creation of the dataset .Random.seed if it does not already exist, otherwise its value is updated.

DETAILS:

Elements of q or p that are missing will cause the corresponding elements of the result to be missing.

For details on the uniform random number generator implemented in S-PLUS, see the set.seed help file.

SEE ALSO:

, .

EXAMPLES:

rpois(20,3)  #sample of size 20 with a mean of 3