CDF.Rd
\name{CDF}
\alias{CDF}
\alias{CDF.density}
\title{
Cumulative Distribution Function From Kernel Density Estimate
}
\description{
Given a kernel estimate of a probability density,
compute the corresponding cumulative distribution function.
}
\usage{
CDF(f, \dots)
\method{CDF}{density}(f, \dots, warn = TRUE)
}
\arguments{
\item{f}{
Density estimate (object of class \code{"density"}).
}
\item{\dots}{
Ignored.
}
\item{warn}{
Logical value indicating whether to issue a warning if the
density estimate \code{f} had to be renormalised because it
was computed in a restricted interval.
}
}
\details{
\code{CDF} is generic, with a method for class \code{"density"}.
This calculates the cumulative distribution function
whose probability density has been estimated and stored in the object
\code{f}. The object \code{f} must belong to the class \code{"density"},
and would typically have been obtained from a call to the function
\code{\link[stats]{density}}.
}
\value{
A function, which can be applied to any numeric value or vector of
values.
}
\author{
\spatstatAuthors
}
\seealso{
\code{\link[stats]{density}},
\code{\link{quantile.density}}
}
\examples{
b <- density(runif(10))
f <- CDF(b)
f(0.5)
plot(f)
}
\keyword{nonparametric}
\keyword{univar}