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\name{plot.edf}
\title{Plot Circular Empirical Distribution Function}
\alias{plot.edf}
\alias{lines.edf}
\description{
Plots the empirical distribution function of a circular data set.
}
\usage{
\method{plot}{edf}(x, type = "s", xlim = c(0, 2 * pi), ylim = c(0, 1), \dots)
\method{lines}{edf}(x, type = "s", \dots)
}
\arguments{
\item{x}{vector of circular data measured.}
\item{type, xlim, ylim}{plotting parameters with useful defaults. \code{xlim} is in radians.}
\item{\dots}{optional graphical parameters. See help section on \code{\link{par}}.}
}
\note{
Creates a plot or adds a plot (\code{lines.edf}) of the empirical
distribution function of the circular data vector.
}
\details{
The vector of data is taken modulo 2*pi, and then the linear ranks are used to generate an empirical distribution function.
}
\author{Claudio Agostinelli and Ulric Lund}
\seealso{
\code{\link{plot.ecdf}}, \code{\link{curve.circular}} and \code{\link{par}}.
}
\examples{
# Compare the edf's of two simulated sets of data.
data1 <- rvonmises(n=10, mu=circular(0), kappa=3)
data2 <- rvonmises(n=10, mu=circular(0), kappa=1)
plot.edf(data1, xlab="Data", ylab="EDF", main="Plots of Two EDF's")
lines.edf(data2, lty=2, col=2)
#You can use standard ecdf and plot.ecdf functions
ff <- function(x, data) {
x <- x%%(2*pi)
data <- data%%(2*pi)
temp <- ecdf(data)
temp(x)
}
plot(function(x) ff(x, data=data1), from=0, to=2*pi-3*.Machine$double.eps)
#Or curve.circular
plot.function.circular(function(x) ff(x, data=data1), from=0,
to=(2*pi-3*.Machine$double.eps), join=FALSE, nosort=TRUE, xlim=c(-2,2),
ylim=c(-2,2), modulo="asis", main="Empirical Distribution Function",
n=2001, tcl.text=0.25)
res <- plot.function.circular(function(x) ff(x, data=data2), from=0,
to=(2*pi-3*.Machine$double.eps), join=FALSE, nosort=TRUE, modulo="asis",
add=TRUE, col=2, n=2001)
res1 <- points(data1, plot.info=res)
points(data2, plot.info=res1, col=2, sep=0.05)
legend(-1.9, 1.9, legend=c("data1", "data2"), col=c(1,2), lty=c(1,1))
}
\keyword{hplot}
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