Plot for kernel cumulative distribution estimate
Plot for kernel cumulative distribution estimate 1- to 3-dimensional data.
## S3 method for class 'kcde' plot(x, ...)
For kcde objects, the function headers for the different dimensional data are
## univariate
plot(Fhat, xlab, ylab="Distribution function", add=FALSE, drawpoints=FALSE,
col.pt="blue", jitter=FALSE, ...)
## bivariate
plot(Fhat, display="persp", cont=seq(10,90, by=10), abs.cont, xlab, ylab,
zlab="Distribution function", cex=1, pch=1, add=FALSE, drawpoints=FALSE,
drawlabels=TRUE, theta=-30, phi=40, d=4, col.pt="blue", col, col.fun,
lwd=1, border=NA, thin=1, lwd.fc=5, ...)
## trivariate
plot(Fhat, display="plot3D", cont=c(25,50,75), colors, col, alphavec, size=3,
cex=1, pch=1, theta=-30, phi=40, d=4, ticktype="detailed", bty="f",
col.pt="blue", add=FALSE, xlab, ylab, zlab, drawpoints=FALSE, alpha,
box=TRUE, axes=TRUE, ...)Plots for 1-d and 2-d are sent to graphics window. Plot for 3-d is sent to graphics/RGL window.
library(MASS) data(iris) Fhat <- kcde(x=iris[,1]) plot(Fhat, xlab="Sepal.Length") Fhat <- kcde(x=iris[,1:2]) plot(Fhat, thin=3) Fhat <- kcde(x=iris[,1:3]) plot(Fhat, alpha=0.3)
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