Fit a Poisson cluster process
The function fits a Poisson cluster process to point data for a given enclosing polygon and fit parameters
pcp(point.data, poly.data, h0=NULL, expo=0.25, n.int=20)
point.data |
a points object |
poly.data |
a polygon enclosing the study region |
h0 |
upper bound of integration in the criterion function |
expo |
exponent in the criterion function |
n.int |
number of intervals used to approximate the integral in the criterion function with a sum |
The function returns an object as returned by optim, including:
par |
The best set of parameters s2 and rho found |
value |
The value of the fit corresponding to ‘par’ |
convergence |
‘0’ indicates successful convergence |
Giovanni Petris <GPetris@uark.edu>, Roger.Bivand@nhh.no
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.
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.fitPlease choose more modern alternatives, such as Google Chrome or Mozilla Firefox.