Visualization of Binary Regression Trees
plot
method for BinaryTree
objects with
extended facilities for plugging in panel functions.
## S3 method for class 'BinaryTree' plot(x, main = NULL, type = c("extended", "simple"), terminal_panel = NULL, tp_args = list(), inner_panel = node_inner, ip_args = list(), edge_panel = edge_simple, ep_args = list(), drop_terminal = (type[1] == "extended"), tnex = (type[1] == "extended") + 1, newpage = TRUE, pop = TRUE, ...)
x |
an object of class |
main |
an optional title for the plot. |
type |
a character specifying the complexity of the plot:
|
terminal_panel |
an optional panel function of the form
|
tp_args |
a list of arguments passed to |
inner_panel |
an optional panel function of the form
|
ip_args |
a list of arguments passed to |
edge_panel |
an optional panel function of the form
|
ep_args |
a list of arguments passed to |
drop_terminal |
a logical indicating whether all terminal nodes should be plotted at the bottom. |
tnex |
a numeric value giving the terminal node extension in relation to the inner nodes. |
newpage |
a logical indicating whether |
pop |
a logical whether the viewport tree should be popped before return. |
... |
additional arguments passed to callies. |
This plot
method for BinaryTree
objects provides an
extensible framework for the visualization of binary regression trees. The
user is allowed to specify panel functions for plotting terminal and inner
nodes as well as the corresponding edges. Panel functions for plotting
inner nodes, edges and terminal nodes are available for the most important
cases and can serve as the basis for user-supplied extensions, see
node_inner
and vignette("party")
.
More details on the ideas and concepts of panel-generating functions and
"grapcon_generator"
objects in general can be found in Meyer, Zeileis
and Hornik (2005).
David Meyer, Achim Zeileis, and Kurt Hornik (2006). The Strucplot Framework: Visualizing Multi-Way Contingency Tables with vcd. Journal of Statistical Software, 17(3). doi: 10.18637/jss.v017.i03
set.seed(290875) airq <- subset(airquality, !is.na(Ozone)) airct <- ctree(Ozone ~ ., data = airq) ### regression: boxplots in each node plot(airct, terminal_panel = node_boxplot, drop_terminal = TRUE) if(require("TH.data")) { ## classification: barplots in each node data("GlaucomaM", package = "TH.data") glauct <- ctree(Class ~ ., data = GlaucomaM) plot(glauct) plot(glauct, inner_panel = node_barplot, edge_panel = function(ctreeobj, ...) { function(...) invisible() }, tnex = 1) ## survival: Kaplan-Meier curves in each node data("GBSG2", package = "TH.data") library("survival") gbsg2ct <- ctree(Surv(time, cens) ~ ., data = GBSG2) plot(gbsg2ct) plot(gbsg2ct, type = "simple") }
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.