feature (version 1.2.13)

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 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

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,addSignifGradData

flag for display of significant gradient regions/data points

addSignifCurvRegion,addSignifCurvData

flag for display of significant curvature regions/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/data points

curvCol

colour of significant curvature regions/data points

axisCol

colour of axes

bgCol

colour of background

dataAlpha

transparency of data points

gradRegionAlpha,gradDataAlpha

transparency of significant gradient regions/data points

curvRegionAlpha,curvDataAlpha

transparency of significant curvature regions/data points

...

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

# NOT RUN {
## See ? featureSignif for uni- and bivariate examples
## Trivariate example
# }
# NOT RUN {
data(earthquake)
earthquake[,3] <- -log10(-earthquake[,3])
fs <- featureSignif(earthquake, scaleData=TRUE, bw=c(0.06, 0.06, 0.05))
plot(fs, addKDE=FALSE, addSignifCurvRegion=TRUE)
# }