https://github.com/cran/spatstat
Tip revision: 557291f3fe7c263c28aba1fe2c6b4b8fc12047ab authored by Adrian Baddeley on 04 November 2018, 16:10:03 UTC
version 1.57-1
version 1.57-1
Tip revision: 557291f
linim.Rd
\name{linim}
\alias{linim}
\title{
Create Pixel Image on Linear Network
}
\description{
Creates an object of class \code{"linim"} that represents
a pixel image on a linear network.
}
\usage{
linim(L, Z, \dots, restrict=TRUE, df=NULL)
}
\arguments{
\item{L}{
Linear network (object of class \code{"linnet"}).
}
\item{Z}{
Pixel image (object of class \code{"im"}).
}
\item{\dots}{Ignored.}
\item{restrict}{
Advanced use only.
Logical value indicating whether to ensure that all pixels in \code{Z}
which do not lie on the network \code{L} have pixel value \code{NA}.
This condition must be satisfied, but if you set
\code{restrict=FALSE} it will not be checked, and the code will
run faster.
}
\item{df}{
Advanced use only. Data frame giving full details of the mapping between
the pixels of \code{Z} and the lines of \code{L}.
See Details.
}
}
\details{
This command creates an object of class \code{"linim"} that represents
a pixel image defined on a linear network.
Typically such objects are
used to represent the result of smoothing or model-fitting on the
network. Most users will not need to call \code{linim} directly.
The argument \code{L} is a linear network (object of class \code{"linnet"}).
It gives the exact spatial locations
of the line segments of the network, and their connectivity.
The argument \code{Z} is a pixel image object of class \code{"im"}
that gives a pixellated approximation of the function values.
For increased efficiency, advanced users may specify the
optional argument \code{df}. This is a data frame giving the
precomputed mapping between the pixels of \code{Z}
and the line segments of \code{L}.
It should have columns named \code{xc, yc} containing the coordinates of
the pixel centres, \code{x,y} containing the projections of these
pixel centres onto the linear network, \code{mapXY} identifying the
line segment on which each projected point lies, and \code{tp} giving
the parametric position of \code{(x,y)} along the segment.
}
\value{
Object of class \code{"linim"} that also inherits the class
\code{"im"}.
There is a special method for plotting this class.
}
\author{
\adrian
}
\seealso{
\code{\link{plot.linim}},
\code{\link{linnet}},
\code{\link{eval.linim}},
\code{\link{Math.linim}},
\code{\link{im}}.
}
\examples{
Z <- as.im(function(x,y) {x-y}, Frame(simplenet))
X <- linim(simplenet, Z)
X
}
\references{
Ang, Q.W. (2010)
\emph{Statistical methodology for events on a network}.
Master's thesis, School of Mathematics and Statistics, University of
Western Australia.
Ang, Q.W., Baddeley, A. and Nair, G. (2012)
Geometrically corrected second-order analysis of
events on a linear network, with applications to
ecology and criminology.
\emph{Scandinavian Journal of Statistics} \bold{39}, 591--617.
McSwiggan, G., Nair, M.G. and Baddeley, A. (2012)
Fitting Poisson point process models to events
on a linear network. Manuscript in preparation.
}
\keyword{spatial}