| plot.edf {circular} | R Documentation |
Plots the empirical distribution function of a circular data set.
## S3 method for class 'edf': plot(x, type = "s", xlim = c(0, 2 * pi), ylim = c(0, 1), ...) ## S3 method for class 'edf': lines(x, type = "s", ...)
x |
vector of circular data measured. |
type, xlim, ylim |
plotting parameters with useful defaults. xlim is in radians. |
... |
optional graphical parameters. See help section on par. |
The vector of data is taken modulo 2*pi, and then the linear ranks are used to generate an empirical distribution function.
Creates a plot or adds a plot (lines.edf) of the empirical
distribution function of the circular data vector.
Claudio Agostinelli and Ulric Lund
plot.ecdf, curve.circular and par.
# 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
data <- data
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))