rpoistpp: Simulating temporal poisson point patterns

In stlnpp: Spatio-Temporal Analysis of Point Patterns on Linear Networks

Simulating temporal poisson point patterns

Description

simulating realisations of a temporal poisson point process.

Usage

rpoistpp(lambda,a,b,check=FALSE,lmax=NULL,nsim=1)

Arguments

lambda	intensity of the point process. It can be either a number, a function of location and time, or an object of class tppint.
a	lower bound of time period.
b	upper bound of time period.
check	Logical value indicating whether to check that all the points lie inside the specified time period.
lmax	upper bound for the values of labmda. This is optinal.
nsim	number of simulated patterns to generate.

Details

This function generates realisations of a temporal poisson point process based on a given intensity function lambda and lower/upper bounds a and b.

Value

an object of class tpp if nsim=1, otherwise a list of objects of class tpp.

Author(s)

Mehdi Moradi <[e-mail]>

References

Moradi, M.M. and Mateu, J. (2019). First and second-order characteristics of spatio-temporal point processes on linear networks. Journal of Computational and Graphical Statistics. In press.

See Also

rpoistlpp

Examples

f <- function(t){0.1*exp(t)}
X <- rpoistpp(f,a=1,b=10)

stlnpp documentation built on Nov. 11, 2022, 9:11 a.m.