fitted model object of class "tree".
This is assumed to be the result of some function that produces
an object with the same
components as that returned by the tree function.
...:
any number of variables to view. Each variable must be have a name from those in
the names attribute of the data frame used in fitting tree.
OPTIONAL ARGUMENTS:
nodes=:
an integer containing the index (node number)
of the node to be examined.
If missing, user selects nodes interactively as described below.
screen.arg=:
integer denoting the screen to be used for the histogram plotting. By default
the active current screen plus one is used.
See split.screen and tree.screens for more details.
figs=:
the arrangement of sub-screens to further split the histogram screen for the
plotting of the individual variable histograms. Generally, a vector of the
form c(n,m) where n and m are integers.
plot=:
logical flag; if nodes is given, should the histogram be plotted?
VALUE:
an invisible (unless plot=FALSE)
list with names from ... for the last node selected interactively
or the one given in the argument nodes.
Each component of this list is a list itself with two components
with names x (the values going left) and y (the values going right).
SIDE EFFECTS:
For each node selected and for each of the variables in ...,
a horizontal histogram of the
observations going left is placed opposite to a histogram of the observations
going to the right.
GRAPHICAL:
This function checks that the user is in split-screen mode.
A dendrogram of tree is expected to be visible on the current active screen,
and a graphics input device (for example, a mouse) is required.
Clicking the selection button on a node results in the additional screens
being filled with the information described above.
This process may be repeated any number of times.
Warnings result from selecting leaf nodes.
Clicking the exit button will stop the display process
and return the list described above for the last node selected.
See split.screen for specific details on graphic input
and split-screen mode.
NOTE:
You may need to attach the original data frame prior to using this function.