feature (version 1.2.2)

plot.fs: Feature signficance plot for 1- to 3-dimensional data

Description

Feature signficance plot for 1- to 3-dimensional data.

Usage

## S3 method for class 'fs':
plot(x, ..., xlab, ylab, zlab, xlim, ylim, zlim,
   add=FALSE, addData=FALSE, scaleData=FALSE, addDataNum=1000,
   addKDE=TRUE, jitterRug=TRUE,  
   addSignifGradRegion=FALSE, addSignifGradData=FALSE,
   addSignifCurvRegion=FALSE, addSignifCurvData=FALSE,
   addAxes3d=TRUE, densCol, dataCol="black", gradCol="green4",
   curvCol="blue", axisCol="black", bgCol="white",
   dataAlpha=0.1, gradDataAlpha=0.3, gradRegionAlpha=0.2,
   curvDataAlpha=0.3, curvRegionAlpha=0.3)

Arguments

x

an object of class fs (output from featureSignif function)

xlim, ylim, zlim

x-, y-, z-axis limits

xlab, ylab, zlab

x-, y-, z-axis labels

scaleData

flag for scaling the data i.e. transforming to unit variance for each dimension

add

flag for adding to an existing plot

addData

flag for display of the data

addDataNum

maximum number of data points plotted in displays

addKDE

flag for display of kernel density estimates

jitterRug

flag for jittering of rug-plot for univariate data display

addSignifGradRegion

flag for display of significant gradient regions

addSignifGradData

flag for display of significant gradient data points

addSignifCurvRegion

flag for display of significant curvature regions

addSignifCurvData

flag for display of significant curvature data points

addAxes3d

flag for displaying axes in 3-d displays

densCol

colour of density estimate curve

dataCol

colour of data points

gradCol

colour of significant gradient regions points

curvCol

colour of significant curvature regions points

axisCol

colour of axes

bgCol

colour of background

dataAlpha

transparency of data points

gradDataAlpha

transparency of significant gradient data points

gradRegionAlpha

transparency of significant gradient regions

curvDataAlpha

transparency of significant curvature data points

curvRegionAlpha

transparency of significant curvature regions

...

other graphics parameters

Value

• Plot of 1-d and 2-d kernel density estimates are sent to graphics window. Plot for 3-d is sent to RGL window.

See Also

featureSignif

Examples

library(MASS)
data(geyser)
fs <- featureSignif(geyser, bw=c(4.5, 0.37))
plot(fs, addKDE=FALSE, addData=TRUE)  ## data only
plot(fs, addKDE=TRUE)                 ## KDE plot only
plot(fs, addSignifGradRegion=TRUE)    
plot(fs, addKDE=FALSE, addSignifCurvRegion=TRUE)
plot(fs, addSignifCurvData=TRUE, curvCol="cyan")