by.ppp.Rd
\name{by.ppp}
\alias{by.ppp}
\title{Apply a Function to a Point Pattern Broken Down by Factor}
\description{
Splits a point pattern into sub-patterns, and applies the function to each
sub-pattern.
}
\usage{
\method{by}{ppp}(data, INDICES=marks(data), FUN, ...)
}
\arguments{
\item{data}{Point pattern (object of class \code{"ppp"}).}
\item{INDICES}{Grouping variable. Either a factor, a pixel image with
factor values, or a tessellation.}
\item{FUN}{Function to be applied to subsets of \code{data}.}
\item{\dots}{Additional arguments to \code{FUN}.}
}
\details{
This is a method for the generic function \code{\link{by}}
for point patterns (class \code{"ppp"}).
The point pattern \code{data} is first divided into subsets
according to \code{INDICES}. Then the function \code{FUN}
is applied to each subset. The results of each computation are
returned in a list.
The argument \code{INDICES} may be
\itemize{
\item
a factor, of length equal to the number of points in \code{data}.
The levels of \code{INDICES}
determine the destination of each point in \code{data}.
The \code{i}th point of \code{data} will be placed in the sub-pattern
\code{split.ppp(data)$l} where \code{l = f[i]}.
\item
a pixel image (object of class \code{"im"}) with factor values.
The pixel value of \code{INDICES}
at each point of \code{data} will be used as the classifying variable.
\item
a tessellation (object of class \code{"tess"}).
Each point of \code{data} will be classified according to
the tile of the tessellation into which it falls.
}
If \code{INDICES} is missing, then \code{data} must be a multitype point pattern
(a marked point pattern whose marks vector is a factor).
Then the effect is that the points of each type
are separated into different point patterns.
}
\value{
A list (also of class \code{"listof"}) containing the results returned
from \code{FUN} for each of the subpatterns.
}
\seealso{
\code{\link{ppp}},
\code{\link{split.ppp}},
\code{\link{cut.ppp}},
\code{\link{tess}},
\code{\link{im}}.
}
\examples{
# multitype point pattern, broken down by type
data(amacrine)
by(amacrine, FUN=density)
by(amacrine, FUN=function(x) { min(nndist(x)) } )
# how to pass additional arguments to FUN
by(amacrine, FUN=clarkevans, correction=c("Donnelly","cdf"))
# point pattern broken down by tessellation
data(swedishpines)
tes <- quadrats(swedishpines, 5, 5)
B <- by(swedishpines, tes, clarkevans, correction="Donnelly")
unlist(lapply(B, as.numeric))
}
\author{Adrian Baddeley
\email{Adrian.Baddeley@csiro.au}
\url{http://www.maths.uwa.edu.au/~adrian/}
and Rolf Turner
\email{r.turner@auckland.ac.nz}
}
\keyword{spatial}
\keyword{methods}
\keyword{manip}