R: Fit a Poisson cluster process

pcp {splancs} | R Documentation

## Fit a Poisson cluster process

### Description

The function fits a Poisson cluster process to point data for a given enclosing polygon and fit parameters

### Usage

    pcp(point.data, poly.data, h0=NULL, expo=0.25, n.int=20)

### Arguments

`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

### Value

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

### Author(s)

Giovanni Petris <GPetris@uark.edu>, Roger.Bivand@nhh.no

### 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

`optim`, `pcp.sim`, `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

[Package splancs version 2.01-40 Index]