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\name{bw.voronoi}
\alias{bw.voronoi}
\title{
Cross Validated Bandwidth Selection for Voronoi Estimator of Intensity
on a Network
}
\description{
Uses cross-validation to select a smoothing bandwidth
for the Voronoi estimate of point process intensity
on a linear network.
}
\usage{
bw.voronoi(X, \dots, probrange = c(0.2, 0.8), nprob = 10,
prob = NULL, nrep = 100, verbose = TRUE, warn=TRUE)
}
\arguments{
\item{X}{
Point pattern on a linear network (object of class \code{"lpp"}).
}
\item{\dots}{
Ignored.
}
\item{probrange}{
Numeric vector of length 2 giving the range of bandwidths
(retention probabilities)
to be assessed.
}
\item{nprob}{
Integer. Number of bandwidths to be assessed.
}
\item{prob}{
Optional. A numeric vector of bandwidths (retention probabilities)
to be assessed. Entries must be probabilities between 0 and 1.
Overrides \code{nprob} and \code{probrange}.
}
\item{nrep}{
Number of simulated realisations to be used for the computation.
}
\item{verbose}{
Logical value indicating whether to print progress reports.
}
\item{warn}{
Logical. If \code{TRUE}, issue a warning if the maximum of
the cross-validation criterion occurs at one of the ends of the
search interval.
}
}
\details{
This function uses likelihood cross-validation to choose the optimal value of the
thinning fraction \code{f} (the retention probability)
to be used in the smoothed Voronoi estimator of point process
intensity \code{\link{densityVoronoi.lpp}}.
}
\value{
A single numerical value giving the selected bandwidth.
The result also belongs to the class \code{"bw.optim"}
(see \code{\link[spatstat.explore]{bw.optim.object}})
which can be plotted to show the bandwidth selection criterion
as a function of \code{sigma}.
}
\references{
Moradi, M., Cronie, 0., Rubak, E., Lachieze-Rey, R.,
Mateu, J. and Baddeley, A. (2019)
Resample-smoothing of Voronoi intensity estimators.
\emph{Statistics and Computing} \bold{29} (5) 995--1010.
}
\author{
\spatstatAuthors and \mehdi.
}
\seealso{
\code{\link{densityVoronoi.lpp}}, \code{\link[spatstat.explore]{bw.optim.object}}
}
\examples{
np <- if(interactive()) 10 else 3
nr <- if(interactive()) 100 else 2
b <- bw.voronoi(spiders, nprob=np, nrep=nr)
b
plot(b)
}
\keyword{spatial}
\keyword{methods}
\keyword{smooth}
\concept{Bandwidth selection}
|
