density.psp.Rd
\name{density.psp}
\alias{density.psp}
\title{Kernel Smoothing of Line Segment Pattern}
\description{
Compute a kernel smoothed intensity function from a line segment pattern.
}
\usage{
\method{density}{psp}(x, sigma, \dots, edge=TRUE)
}
\arguments{
\item{x}{
Line segment pattern (object of class \code{"psp"}) to be smoothed.
}
\item{sigma}{
Standard deviation of isotropic Gaussian smoothing kernel.
}
\item{\dots}{
Extra arguments passed to \code{\link{as.mask}} which determine
the resolution of the resulting image.
}
\item{edge}{
Logical flag indicating whether to apply edge correction.
}
}
\value{
A pixel image (object of class \code{"im"}).
}
\details{
This is a method for the generic function \code{\link{density}}.
A kernel estimate of the intensity of the line segment pattern
is computed. The result is
the convolution of the isotropic Gaussian kernel, of
standard deviation \code{sigma}, with the line segments.
Computation is performed analytically.
If \code{edge=TRUE} this result is adjusted for edge effects
by dividing it by the convolution of the same Gaussian kernel
with the observation window.
}
\seealso{
\code{\link{psp.object}},
\code{\link{im.object}},
\code{\link{density}}
}
\examples{
L <- psp(runif(20),runif(20),runif(20),runif(20), window=owin())
D <- density(L, sigma=0.03)
plot(D, main="density(L)")
plot(L, add=TRUE)
}
\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{methods}
\keyword{smooth}