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Last data update: 2014.03.03

R: Plot for kernel local significant difference regions

plot.kde.loctest

R Documentation

Plot for kernel local significant difference regions

Description

Plot for kernel local significant difference regions for 1- to 3-dimensional data.

Usage

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

Arguments

x

an object of class kde.loctest (output from kde.local.test)

...

other graphics parameters:

lcol: colour for KDE curve (1-d)
col: vector of 2 colours. Default is c("purple", "darkgreen"). First colour: sample 1>sample 2, second colour: sample 1<sample2.
add: flag to add to current plot. Default is FALSE.
rugsize: height of rug-like plot (1-d)
add.legend: flag to add legend. Default is FALSE (1-d, 2-d).
pos.legend: position label for legend (1-d, 2-d)
add.contour: flag to add contour lines. Default is FALSE (2-d).

and those used in plot.kde

Details

For kde.loctest objects, the function headers are

   ## univariate
   plot(x, lcol, col, add=FALSE, xlab="x", ylab, rugsize, add.legend=TRUE, 
     pos.legend="topright", ...)
   
   ## bivariate
   plot(x, col, add=FALSE, xlab="x", ylab="y", add.contour=FALSE, 
     add.legend=TRUE, pos.legend="topright", ...)

   ## trivariate 
   plot(x, col, add=FALSE, xlab="x", ylab="y", zlab="z", box=TRUE, axes=TRUE,
     alphavec=c(0.5, 0.5), ...)

Value

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

Examples

library(MASS)
data(crabs)
x1 <- crabs[crabs$sp=="B", c(4,6)]
x2 <- crabs[crabs$sp=="O", c(4,6)]
loct <- kde.local.test(x1=x1, x2=x2)
plot(loct)