plot.kde.loctest: Plot for kernel local significant difference regions

In ks: Kernel Smoothing

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

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. 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 TRUE. pos.legend position label for legend (1-d, 2-d) alphavec vector of transparency values for contour (3-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", alpha=1, ...)
   
   ## bivariate
   plot(x, col, add=FALSE, add.legend=TRUE, pos.legend="topright", alpha=1, 
        ...)

   ## trivariate 
   plot(x, col, color, add=FALSE, box=TRUE, axes=TRUE, alphavec=c(0.5, 0.5), 
        add.legend=TRUE, ...)

Value

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

See Also

kde.local.test

Examples

## bivariate
data(air)
air.var <- c("co2","pm10","no")
air <- air[, c("date","time",air.var)]
air2 <- reshape(air, idvar="date", timevar="time", direction="wide")
a1 <- as.matrix(na.omit(air2[, paste0(air.var, ".08:00")]))
a2 <- as.matrix(na.omit(air2[, paste0(air.var, ".20:00")]))
colnames(a1) <- air.var
colnames(a2) <- air.var
loct <- kde.local.test(x1=a1[,c("co2","pm10")], x2=a2[,c("co2","pm10")])
plot(loct, lwd=1)

## trivariate
loct <- kde.local.test(x1=a1, x2=a2)
plot(loct, xlim=c(0,800), ylim=c(0,300), zlim=c(0,300))

ks documentation built on Sept. 30, 2024, 9:15 a.m.