rpoistrunc {spatstat.random} | R Documentation |
Random Values from the Truncated Poisson Distribution
Description
Generate realisations of a Poisson random variable which are truncated, that is, conditioned to be nonzero, or conditioned to be at least a given number.
Usage
rpoisnonzero(n, lambda, method=c("harding", "transform"), implem=c("R", "C"))
rpoistrunc(n, lambda, minimum = 1, method=c("harding", "transform"), implem=c("R", "C"))
Arguments
n |
Number of random values to be generated. |
lambda |
Mean value of the un-truncated Poisson distribution. A nonnegative number, or vector of nonnegative numbers. |
minimum |
Minimum permitted value for the random variables. A nonnegative integer, or vector of nonnegative integers. |
method |
Character string (partially matched) specifying the simulation algorithm to be used. See Details. |
implem |
Character string specifying whether to use the implementation
in interpreted R code ( |
Details
rpoisnonzero
generates realisations of the
Poisson distribution with mean lambda
conditioned on the event that the values are not equal to zero.
rpoistrunc
generates realisations of the
Poisson distribution with mean lambda
conditioned on the event that the values are greater than
or equal to minimum
.
The default minimum=1
is equivalent to
generating zero-truncated Poisson random variables
using rpoisnonzero
.
The value minimum=0
is equivalent to
generating un-truncated Poisson random variables
using rpois
.
The arguments lambda
and minimum
can be
vectors of length n
, specifying different means
for the un-truncated Poisson distribution, and different
minimum values, for each of the n
random output values.
If method="transform"
the simulated values are generated
by transforming a uniform random variable using the quantile function
of the Poisson distribution.
If method="harding"
(the default) the simulated values are
generated using an algorithm proposed by E.F. Harding which exploits
properties of the Poisson point process. The Harding algorithm seems
to be faster.
Value
An integer vector of length n
.
Author(s)
Adrian Baddeley Adrian.Baddeley@curtin.edu.au, after ideas of Ted Harding and Peter Dalgaard.
See Also
rpois
for Poisson random variables.
recipEnzpois
for the reciprocal moment of rpoisnonzero
.
Examples
rpoisnonzero(10, 0.8)
rpoistrunc(10, 1, 2)