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Plot for kernel local significant difference regions for 1- to 3-dimensional data.
# S3 method for kde.loctest plot(x, ...)
an object of class kde.loctest (output from kde.local.test)
kde.loctest
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
plot.kde
Plots for 1-d and 2-d are sent to graphics window. Plot for 3-d is sent to RGL window.
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), ...)
## 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), ...)
# NOT RUN { 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) # }
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