plot.kde: Plot for kernel density estimate

In ks: Kernel Smoothing

Plot for kernel density estimate

Description

Plot for kernel density estimate for 1- to 3-dimensional data.

Usage

## S3 method for class 'kde'
plot(x, ...)

Arguments

x

object of class kde (output from kde)

...

other graphics parameters: display type of display, "slice" for contour plot, "persp" for perspective plot, "image" for image plot, "filled.contour" for filled contour plot (2-d); "plot3D", "rgl" (3-d) cont vector of percentages for contour level curves abs.cont vector of absolute density estimate heights for contour level curves approx.cont flag to compute approximate contour levels. Default is FALSE. col plotting colour for density estimate (1-d, 2-d) col.cont plotting colour for contours col.fun plotting colour function for contours col.pt plotting colour for data points colors vector of colours for each contour (3-d) jitter flag to jitter rug plot (1-d). Default is TRUE. lwd.fc line width for filled contours (2-d) xlim,ylim,zlim axes limits xlab,ylab,zlab axes labels add flag to add to current plot. Default is FALSE. theta,phi,d,border graphics parameters for perspective plots (2-d) drawpoints flag to draw data points on density estimate. Default is FALSE. drawlabels flag to draw contour labels (2-d). Default is TRUE. alpha transparency value of plotting symbol alphavec vector of transparency values for contours (3-d) size size of plotting symbol (3-d).

Details

For kde objects, the function headers for the different dimensional data are

  ## univariate
  plot(fhat, xlab, ylab="Density function", add=FALSE, drawpoints=FALSE, col=1,
       col.pt=4, col.cont=1, cont.lwd=1, jitter=FALSE, cont, abs.cont, 
       approx.cont=TRUE, alpha=1, ...)
  
  ## bivariate
  plot(fhat, display="slice", cont=c(25,50,75), abs.cont, approx.cont=TRUE, 
       xlab, ylab, zlab="Density function", cex=1, pch=1, add=FALSE, 
       drawpoints=FALSE, drawlabels=TRUE, theta=-30, phi=40, d=4, col.pt=4, 
       col, col.fun, alpha=1, lwd=1, border=1, thin=3, kdde.flag=FALSE, 
       ticktype="detailed", ...) 

  ## trivariate
  plot(fhat, display="plot3D", cont=c(25,50,75), abs.cont, approx.cont=TRUE, 
       colors, col, col.fun, alphavec, size=3, cex=1, pch=1, theta=-30, phi=40, 
       d=4, ticktype="detailed", bty="f", col.pt=4, add=FALSE, xlab, ylab, 
       zlab, drawpoints=FALSE, alpha, box=TRUE, axes=TRUE, ...)

For 1-dimensional data, the plot is a standard plot of a 1-d curve. If drawpoints=TRUE then a rug plot is added. If cont is specified, the horizontal line on the x-axis indicates the cont% highest density level set.

For 2-dimensional data, the different types of plotting displays are controlled by the display parameter. (a) If display="slice" then a slice/contour plot is generated using contour. (b) If display is "filled.contour" then a filled contour plot is generated. The default contours are at 25%, 50%, 75% or cont=c(25,50,75) which are upper percentages of highest density regions. (c) If display="persp" then a perspective/wire-frame plot is generated. The default z-axis limits zlim are the default from the usual persp command. (d) If display="image" then an image plot is generated.

For 3-dimensional data, the plot is a series of nested 3-d contours. The default contours are cont=c(25,50,75). The default opacity alphavec ranges from 0.1 to 0.5. For ks \geq 1.12.0, base R graphics becomes the default plotting engine: to create an rgl plot like in previous versions, set display="rgl".

To specify contours, either one of cont or abs.cont is required. cont specifies upper percentages which correspond to probability contour regions. If abs.cont is set to particular values, then contours at these levels are drawn. This second option is useful for plotting multiple density estimates with common contour levels. See contourLevels for details on computing contour levels. If approx=FALSE, then the exact KDE is computed. Otherwise it is interpolated from an existing KDE grid, which can dramatically reduce computation time for large data sets.

If a colour function is specified in col.fun, it should have the number of colours as a single argument, e.g. function(n){hcl.colors(n, ...)}. The transparent background colour is automatically concatenated before this colour function. If col is specified, it overrides col.fun. There should be one more colour than the number of contours, i.e. background colour plus one for each contour.

Value

Plots for 1-d and 2-d are sent to graphics window. Plot for 3-d is sent to graphics/RGL window.

Examples

data(iris)

## univariate example
fhat <- kde(x=iris[,2])
plot(fhat, cont=50, col.cont=4, cont.lwd=2, xlab="Sepal length")

## bivariate example
fhat <- kde(x=iris[,2:3])
plot(fhat, display="filled.contour", cont=seq(10,90,by=10), lwd=1, alpha=0.5)
plot(fhat, display="persp", border=1, alpha=0.5)

## trivariate example
fhat <- kde(x=iris[,2:4])
plot(fhat)
if (interactive()) plot(fhat, display="rgl")

ks documentation built on Aug. 11, 2023, 1:10 a.m.