Principle Components Plot of a Multivariate Rpart Object

Plots a PCA of the rpart object on the current graphics device.

Usage

# S3 method for class 'pca'
rpart(tree, pts = TRUE, plt.allx = TRUE, speclabs = TRUE,
    specvecs = TRUE, wgt.ave = FALSE, add.tree = TRUE,  
    cv1 = 1, cv2 = 2, chulls = TRUE, interact = FALSE, ...)

Arguments

tree: A fitted object of class rpart containing a multivariate regression tree.
pts: If TRUE, large points representing the leaf means are plotted.
plt.allx: If TRUE, small points representing individual cases are plotted.
speclabs: If TRUE the labels of the response variables are plotted.
specvecs: If TRUE the vectors of the response variables are plotted provided wgt.ave is FALSE .
wgt.ave: If TRUE use weighted averages of responses not vectors.
add.tree: If TRUE add the tree structure to the plot.
cv1: Defines the principal component to plot horizontally – but see interact.
cv2: Defines the principal component to plot vertically – but see interact.
chulls: If TRUE adds convex hulls to thr tree groups.
interact: If TRUE the plot can be viewed in dimensions by left-clicking to top-left, bottom-right or bottom-left (reset).
...: arguments to be passed to or from other methods.

Value

NULL

Side Effects

A PCA biplot plot is produced on the current graphics device.

Details

This function plots a PCA biplot of the group means (leaves) of multivariate regresssion objects of class rpart. The responses and group means and indivdual cases can be shown on the plot. If responses are positive (eg species-environment data) weighted averages of responses can be plotted.

Examples

data(spider)
fit<-mvpart(data.matrix(spider[,1:12])~herbs+reft+moss+sand+twigs+water,spider)

rpart.pca(fit)

rpart.pca(fit,wgt.ave=TRUE,interact=TRUE)