mean.linim.Rd
\name{mean.linim}
\alias{mean.linim}
\alias{median.linim}
\alias{quantile.linim}
\title{Mean, Median, Quantiles of Pixel Values on a Linear Network}
\description{
Calculates the mean, median, or quantiles
of the pixel values in a pixel image on a linear network.
}
\usage{
\method{mean}{linim}(x, \dots)
\method{median}{linim}(x, \dots)
\method{quantile}{linim}(x, probs=seq(0,1,0.25), \dots)
}
\arguments{
\item{x}{
A pixel image on a linear network (object of class
\code{"linim"}).
}
\item{probs}{
Vector of probabilities for which quantiles should be
calculated.
}
\item{\dots}{Arguments passed to other methods.}
}
\details{
These functions calculate the mean, median and quantiles
of the pixel values in the image
\code{x} on a linear network.
An object of class \code{"linim"}
describes a pixel image on a linear network. See \code{\link{linim}}.
The functions described here are methods for the
generic \code{\link{mean}}, \code{\link[stats]{median}}
and \code{\link[stats]{quantile}} for the class \code{"linim"}.
}
\value{
For \code{mean} and \code{median}, a single number.
For \code{quantile}, a numeric vector of the same length as \code{probs}.
}
\seealso{
\code{\link{mean}},
\code{\link[stats]{median}},
\code{\link[stats]{quantile}},
\code{\link{mean.im}}.
}
\examples{
M <- as.mask.psp(as.psp(simplenet))
Z <- as.im(function(x,y) {x-y}, W=M)
X <- linim(simplenet, Z)
X
mean(X)
median(X)
quantile(X)
}
\author{
\spatstatAuthors.
}
\keyword{spatial}
\keyword{methods}
\keyword{univar}