# Panel Generating Functions

##### Panel-Generators for Visualization of Party Trees

The plot method for `BinaryTree`

and `mob`

objects are rather
flexible and can be extended by panel functions. Some pre-defined
panel-generating functions of class `grapcon_generator`

for the most important cases are documented here.

- Keywords
- hplot

##### Usage

```
node_inner(ctreeobj, digits = 3, abbreviate = FALSE,
fill = "white", pval = TRUE, id = TRUE)
node_terminal(ctreeobj, digits = 3, abbreviate = FALSE,
fill = c("lightgray", "white"), id = TRUE)
edge_simple(treeobj, digits = 3, abbreviate = FALSE)
node_surv(ctreeobj, ylines = 2, id = TRUE, …)
node_barplot(ctreeobj, col = "black", fill = NULL, beside = NULL,
ymax = NULL, ylines = NULL, widths = 1, gap = NULL,
reverse = NULL, id = TRUE)
node_boxplot(ctreeobj, col = "black", fill = "lightgray",
width = 0.5, yscale = NULL, ylines = 3, cex = 0.5, id = TRUE)
node_hist(ctreeobj, col = "black", fill = "lightgray",
freq = FALSE, horizontal = TRUE, xscale = NULL, ymax = NULL,
ylines = 3, id = TRUE, …)
node_density(ctreeobj, col = "black", rug = TRUE,
horizontal = TRUE, xscale = NULL, yscale = NULL, ylines = 3,
id = TRUE)
node_scatterplot(mobobj, which = NULL, col = "black",
linecol = "red", cex = 0.5, pch = NULL, jitter = FALSE,
xscale = NULL, yscale = NULL, ylines = 1.5, id = TRUE,
labels = FALSE)
node_bivplot(mobobj, which = NULL, id = TRUE, pop = TRUE,
pointcol = "black", pointcex = 0.5,
boxcol = "black", boxwidth = 0.5, boxfill = "lightgray",
fitmean = TRUE, linecol = "red",
cdplot = FALSE, fivenum = TRUE, breaks = NULL,
ylines = NULL, xlab = FALSE, ylab = FALSE, margins = rep(1.5, 4), …)
```

##### Arguments

- ctreeobj
an object of class

`BinaryTree`

.- treeobj
an object of class

`BinaryTree`

or`mob`

.- mobobj
an object of class

`mob`

.- digits
integer, used for formating numbers.

- abbreviate
logical indicating whether strings should be abbreviated.

- col, pointcol
a color for points and lines.

- fill
a color to filling rectangles.

- pval
logical. Should p values be plotted?

- id
logical. Should node IDs be plotted?

- ylines
number of lines for spaces in y-direction.

- widths
widths in barplots.

- width, boxwidth
width in boxplots.

- gap
gap between bars in a barplot (

`node_barplot`

).- yscale
limits in y-direction

- xscale
limits in x-direction

- ymax
upper limit in y-direction

- beside
logical indicating if barplots should be side by side or stacked.

- reverse
logical indicating whether the order of levels should be reversed for barplots.

- horizontal
logical indicating if the plots should be horizontal.

- freq
logical; if

`TRUE`

, the histogram graphic is a representation of frequencies. If`FALSE`

, probabilities are plotted.- rug
logical indicating if a rug representation should be added.

- which
numeric or character vector indicating which of the regressor variables should be plotted (default = all).

- linecol
color for fitted model lines.

- cex, pointcex
character extension of points in scatter plots.

- pch
plotting character of points in scatter plots.

- jitter
logical. Should the points be jittered in y-direction?

- labels
logical. Should axis labels be plotted?

- pop
logical. Should the panel viewports be popped?

- boxcol
color for box plot borders.

- boxfill
fill color for box plots.

- fitmean
logical. Should lines for the predicted means from the model be added?

- cdplot
logical. Should CD plots (or spinograms) be used for visualizing the dependence of a categorical on a numeric variable?

- fivenum
logical. When using spinograms, should the five point summary of the explanatory variable be used for determining the breaks?

- breaks
a (list of) numeric vector(s) of breaks for the spinograms. If set to

`NULL`

(the default), the`breaks`

are chosen according to the`fivenum`

argument.- xlab, ylab
character with x- and y-axis labels. Can also be logical: if

`FALSE`

axis labels are surpressed, if`TRUE`

they are taken from the underlying data. Can be a vector of labels for`xlab`

.- margins
margins of the viewports.

- …
additional arguments passed to callies.

##### Details

The `plot`

methods for `BinaryTree`

and `mob`

objects provide 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. The panel functions to be used
should depend only on the node being visualzied, however, for setting up
an appropriate panel function, information from the whole tree is typically
required. Hence, party adopts the framework of `grapcon_generator`

(graphical appearance control) from the vcd package (Meyer, Zeileis and
Hornik, 2005) and provides several panel-generating functions. For convenience,
the panel-generating functions `node_inner`

and `edge_simple`

return panel functions to draw inner nodes and left and right edges.
For drawing terminal nodes, the functions returned by the other panel
functions can be used. The panel generating function `node_terminal`

is a terse text-based representation of terminal nodes.

Graphical representations of terminal nodes are available and depend on the kind of model and the measurement scale of the variables modelled.

For univariate regressions (typically fitted by `ctree`

),
`node_surv`

returns a functions that plots Kaplan-Meier curves in each
terminal node; `node_barplot`

, `node_boxplot`

, `node_hist`

and
`node_density`

can be used to plot bar plots, box plots, histograms and
estimated densities into the terminal nodes.

For multivariate regressions (typically fitted by `mob`

),
`node_bivplot`

returns a panel function that creates bivariate plots
of the response against all regressors in the model. Depending on the scale
of the variables involved, scatter plots, box plots, spinograms (or CD plots)
and spine plots are created. For the latter two `spine`

and
`cd_plot`

from the vcd package are re-used.

##### References

David Meyer, Achim Zeileis, and Kurt Hornik (2006).
The Strucplot Framework: Visualizing Multi-Way Contingency Tables with vcd.
*Journal of Statistical Software*, **17**(3).
http://www.jstatsoft.org/v17/i03/

##### Examples

```
# NOT RUN {
set.seed(290875)
airq <- subset(airquality, !is.na(Ozone))
airct <- ctree(Ozone ~ ., data = airq)
## default: boxplots
plot(airct)
## change colors
plot(airct, tp_args = list(col = "blue", fill = hsv(2/3, 0.5, 1)))
## equivalent to
plot(airct, terminal_panel = node_boxplot(airct, col = "blue",
fill = hsv(2/3, 0.5, 1)))
### very simple; the mean is given in each terminal node
plot(airct, type = "simple")
### density estimates
plot(airct, terminal_panel = node_density)
### histograms
plot(airct, terminal_panel = node_hist(airct, ymax = 0.06,
xscale = c(0, 250)))
# }
```

*Documentation reproduced from package party, version 1.3-3, License: GPL-2*