feature (version 1.1-7)

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,
   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, gridsize)

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. Default is FALSE.

addData

flag for display of the data. Default is FALSE.

addDataNum

maximum number of data points plotted in displays. Default is 1000.

addKDE

flag for display of kernel density estimates. Default is TRUE. Not available for 4-d data.

jitterRug

flag for jittering of rug-plot for univariate data display. Default is TRUE.

addSignifGradRegion

flag for display of significant gradient regions. Default is FALSE. Not available for 4-d data.

addSignifGradData

flag for display of significant gradient data points. Default is FALSE.

addSignifCurvRegion

flag for display of significant curvature regions. Default is FALSE. Not available for 4-d data.

addSignifCurvData

flag for display of significant curvature data points. Default is FALSE.

addAxes3d

flag for displaying axes in 3-d displays. Default is TRUE.

densCol

colour of density estimate curve. Default for 1-d data "DarkOrange", for 2-d data is heat.colors(1000), for 3-d data is heat.colors(5).

dataCol

colour of data points. Default is "black".

gradCol

colour of significant gradient regions/points. Default is "green4".

curvCol

colour of significant curvature regions/points. Default is "blue".

axisCol

colour of axes. Default is "black".

bgCol

colour of background. Default is "white".

dataAlpha

alpha-blending transparency value for data points.

gradDataAlpha

alpha-blending transparency value for significant gradient data points.

gradRegionAlpha

alpha-blending transparency value for significant gradient regions.

curvDataAlpha

alpha-blending transparency value for significant curvature data points.

curvRegionAlpha

alpha-blending transparency value for significant curvature regions.

gridsize

vector of the number of grid points in each direction.

...

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.

synopsis

## S3 method for class 'fs': plot(x, ...)

Details

This plotting function is called automatically from inside featureSignif.

Its other primary use is with fs objects created from featureSignif. If the user creates an fs object with the significant gradient and curvature, then it is easier and more efficient to modify the graphical display using plot.fs than to recompute the everything with a call to featureSignif. See examples below.

References

Chaudhuri, P. and Marron, J.S. (1999) SiZer for exploration of structures in curves. Journal of the American Statistical Association, 94, 807-823.

Duong, T., Cowling, A., Koch, I., Wand, M.P. (2006) Feature significance for multivariate kernel density estimation. Submitted. Godtliebsen, F., Marron, J.S. and Chaudhuri, P. (2002) Significance in scale space for bivariate density estimation. Journal of Computational and Graphical Statistics, 11, 1-22.

See Also

featureSignif

Examples

library(MASS)
data(geyser)

fs <- featureSignif(geyser, addSignifGradRegion=TRUE,
     addSignifCurvRegion=TRUE, 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")