pcp.sim: Generate a Poisson Cluster Process

In splancs: Spatial and Space-Time Point Pattern Analysis

Generate a Poisson Cluster Process

Description

The function generates a Poisson cluster process for a given polygon within a larger bounding region and given process parameters

Usage

pcp.sim(rho, m, s2, region.poly, larger.region=NULL, vectorise.loop=TRUE)

Arguments

rho	intensity of the parent process
m	average number of offsprings per parent
s2	variance of location of offsprings relative to their parent
region.poly	a polygon defining the region in which the process is to be generated
larger.region	a rectangle containing the region of interest given in the form (xl,xu,yl,yu), defaults to sbox() around region.poly
vectorise.loop	if TRUE, use new vectorised code, if FALSE, use loop as before

Details

The function generates the parents in the larger bounding region, generates their children also in the larger bounding region, and then returns those inside the given polygon.

Value

A point object with the simulated pattern

Author(s)

Giovanni Petris <[e-mail]>, [e-mail]

References

Diggle, P. J. (1983) Statistical analysis of spatial point patterns, London: Academic Press, pp. 55-57 and 78-81; Bailey, T. C. and Gatrell, A. C. (1995) Interactive spatial data analysis, Harlow: Longman, pp. 106-109.

See Also

pcp, Kenv.pcp, khat

Examples

data(cardiff)
polymap(cardiff$poly)
pointmap(as.points(cardiff), add=TRUE)
title("Locations of homes of 168 juvenile offenders")
pcp.fit <- pcp(as.points(cardiff), cardiff$poly, h0=30, n.int=30)
pcp.fit
m <- npts(as.points(cardiff))/(areapl(cardiff$poly)*pcp.fit$par[2])
sims <- pcp.sim(pcp.fit$par[2], m, pcp.fit$par[1], cardiff$poly)
pointmap(as.points(sims), add=TRUE, col="red")

splancs documentation built on May 29, 2024, 6:22 a.m.