predict.kppm.Rd
\name{predict.kppm}
\alias{predict.kppm}
\title{Prediction from a Fitted Cluster Point Process Model}
\description{
Given a fitted cluster point process model,
this function computes the fitted intensity of the model.
}
\usage{
\method{predict}{kppm}(object, ...)
}
\arguments{
\item{object}{
Fitted cluster point process model.
An object of class \code{"kppm"}.
}
\item{\dots}{Arguments passed to \code{\link{predict.ppm}}.}
}
\details{
This is a method for the generic function \code{\link{predict}}.
The argument \code{object} should be a cluster point process model
(object of class \code{"kppm"}) obtained using
the function \code{\link{kppm}}.
Prediction computes the \emph{intensity} of the fitted model.
The algorithm calls \code{\link{predict.ppm}} to compute the
intensity.
}
\value{
Usually a pixel image (object of class \code{"im"}).
}
\seealso{
\code{\link{kppm}},
\code{\link{plot.kppm}},
\code{\link{predict.ppm}}
}
\examples{
data(redwood)
fit <- kppm(redwood, ~x, "Thomas")
v <- predict(fit)
}
\author{Adrian Baddeley
\email{adrian@maths.uwa.edu.au}
\url{http://www.maths.uwa.edu.au/~adrian/}
and Rolf Turner
\email{r.turner@auckland.ac.nz}
}
\keyword{spatial}
\keyword{models}