subfits.Rd
\name{subfits}
\alias{subfits}
\alias{subfits.new}
\alias{subfits.old}
\title{Extract List of Individual Point Process Models}
\description{
Takes a Gibbs point process model that has been fitted
to several point patterns simultaneously, and produces a list
of fitted point process models for the individual point patterns.
}
\usage{
subfits(object, what="models", verbose=FALSE)
subfits.old(object, what="models", verbose=FALSE)
subfits.new(object, what="models", verbose=FALSE)
}
\arguments{
\item{object}{
An object of class \code{"mppm"}
representing a point process model fitted to several point patterns.
}
\item{what}{
What should be returned.
Either \code{"models"} to return the fitted models,
or \code{"interactions"} to return the fitted interactions only.
}
\item{verbose}{
Logical flag indicating whether to print progress reports.
}
}
\details{
\code{object} is assumed to have been generated by
\code{\link{mppm}}. It represents a point process model that has been
fitted to a list of several point patterns, with covariate data.
For each of the \emph{individual} point pattern
datasets, this function derives the corresponding fitted model
for that dataset only (i.e. a point process model for the \eqn{i}th
point pattern, that is consistent with \code{object}).
If \code{what="models"},
the result is a list of point process models (a list of objects of class
\code{"ppm"}), one model for each point pattern dataset in the
original fit.
If \code{what="interactions"},
the result is a list of fitted interpoint interactions (a list of
objects of class
\code{"fii"}).
Two different algorithms are provided, as
\code{subfits.old} and \code{subfits.new}.
Currently \code{subfits} is the same as the old algorithm
\code{subfits.old} because the newer algorithm is too memory-hungry.
}
\value{
A list of point process models (a list of objects of class
\code{"ppm"}) or a list of fitted interpoint interactions (a list of
objects of class \code{"fii"}).
}
\examples{
H <- hyperframe(Wat=waterstriders)
fit <- mppm(Wat~x, data=H)
subfits(fit)
H$Wat[[3]] <- rthin(H$Wat[[3]], 0.1)
fit2 <- mppm(Wat~x, data=H, random=~1|id)
subfits(fit2)
}
\references{
Baddeley, A., Rubak, E. and Turner, R. (2015)
\emph{Spatial Point Patterns: Methodology and Applications with R}.
London: Chapman and Hall/CRC Press.
}
\author{
Adrian Baddeley, Ida-Maria Sintorn and Leanne Bischoff.
Implemented in \pkg{spatstat} by
\spatstatAuthors.
}
\seealso{
\code{\link{mppm}},
\code{\link{ppm}}
}
\keyword{spatial}
\keyword{models}