plot.fs {feature} | R Documentation |
Feature signficance plot for 1- to 3-dimensional data.
## 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)
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. |
... |
other graphics parameters |
This is a plot method for fs
objects created from
featureSignif
. This plotting function is called
automatically from inside
featureSignif
except when plotFS=FALSE
.
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 just using plot.fs
. See
examples below.
Plot of 1-d and 2-d kernel density estimates are sent to graphics window. Plot for 3-d is sent to RGL window.
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. (2007) 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.
library(MASS) data(geyser) fs <- featureSignif(geyser, addSignifGradRegion=TRUE, addSignifCurvRegion=TRUE, bw=c(4.5, 0.37), plotFS=FALSE) 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")