biplot3D {compositions} | R Documentation |
Plots variables and cases in the same plot, based on a principal component analysis.
biplot3D(x,...) ## Default S3 method: biplot3D(x,y,var.axes=TRUE,col=c("green","red"),cex=c(2,2), xlabs = NULL, ylabs = NULL, expand = 1,arrow.len = 0.1, ...,add=FALSE) ## S3 method for class 'princomp': biplot3D(x,choices=1:3,scale=1,..., comp.col=par("fg"),comp.labs=paste("Comp.",1:3), scale.scores=lambda[choices]^(1-scale), scale.var=scale.comp, scale.comp=sqrt(lambda[choices]), scale.disp=1/scale.comp)
x |
princomp object or matrix of point locations to be drawn (typically, cases) |
choices |
Which principal components should be used? |
scale |
a scaling parameter like in biplot |
scale.scores |
a vector giving the scaling applied to the scores |
scale.var |
a vector giving the scaling applied to the variables |
scale.comp |
a vector giving the scaling applied to the unit length of each component |
scale.disp |
a vector giving the scaling of the display in the directions of the components |
comp.col |
color to draw the axes of the components |
comp.labs |
labels for the components |
... |
further plotting parameters as defined in rgl.material |
y |
matrix of second point/arrow-head locations (typically, variables) |
var.axes |
logical, TRUE draws arrows and FALSE points for y |
col |
vector/list of two elements the first giving the color/colors for the first data set and the second giving color/colors for the second data set. |
cex |
vector/list of two elements the first giving the size for the first data set and the second giving size for the second data set. |
xlabs |
labels to be plotted at x-locations |
ylabs |
labels to be plotted at y-locations |
expand |
the relative expansion of the y data set with respect to x |
arrow.len |
The length of the arrows as defined in arrows3D |
add |
logical, adding to existing plot or making a new one? |
This "biplot" is a triplot, relating data, variables and principal components. The relative scaling of the components is still experimental, meant to mimic the behavior of classical biplots.
nothing
K.Gerald v.d. Boogaart http://www.stat.boogaart.de
data(SimulatedAmounts) pc <- princomp(acomp(sa.lognormals5)) pc summary(pc) plot(pc) #plot(pc,type="screeplot") biplot3D(pc)