plot.TSVC: Plotting of Varying Coefficient Trees

In TSVC: Tree-Structured Modelling of Varying Coefficients

Plotting of Varying Coefficient Trees

Description

Visualization of trees of effects of covariates that vary with the values of one or several effect modifiers.

Usage

## S3 method for class 'TSVC'
plot(
  x,
  variable,
  ellipse_a = 0.8,
  ellipse_b = 0.2,
  ellipse_x = 0,
  ellipse_y = 0,
  branch_adj = 0,
  cex.lines = 2,
  cex.branches = 1,
  cex.coefs = 1,
  cex.main = 1,
  cex.numbers = 1,
  draw_numbers = TRUE,
  title = NULL,
  decimals = 3,
  confint = NULL,
  ...
)

Arguments

x	a fitted object of class TSVC.
variable	name of the variable, for which the tree shall be plotted.
ellipse_a	controls width of ellipses containing coefficient estimates.
ellipse_b	controls height of ellipses containing coefficient estimates.
ellipse_x	controls location on x-axis of ellipses containing coefficient estimates.
ellipse_y	controls location on y-axis of ellipses containing coefficient estimates.
branch_adj	vertical adjustment of branch labels.
cex.lines	width of branches of the tree.
cex.branches	size of the labels of the tree.
cex.coefs	size of the coefficients in the terminal nodes of the tree.
cex.main	size of the title of the tree.
cex.numbers	size of the internally used node number.
draw_numbers	if true, internally used node numbers are displayed.
title	optional title, which is addded to the tree; if title=NULL the title is the name of the variable in the data.
decimals	number of decimals of coefficient estimates. Per default the coefficient estimates are displayed with three decimals.
confint	optional fitted object of class confint.TSVC with confidence intervals to be plotted in the terminal nodes of the tree; if confint=NULL (default) only the coefficient estimates will be plotted.
...	further arguments passed to or from other methods.

Author(s)

Moritz Berger <[e-mail]>
https://www.imbie.uni-bonn.de/people/dr-moritz-berger/

References

Berger, M., G. Tutz and M. Schmid (2019). Tree-Structured Modelling of Varying Coefficients. Statistics and Computing 29, 217-229, https://doi.org/10.1007/s11222-018-9804-8.

See Also

TSVC, predict.TSVC, summary.TSVC

Examples

# Swiss Labour Market 
library(AER)
data("SwissLabor")

# recode factors 
sl <- SwissLabor
sl$participation <- as.numeric(sl$participation)-1
sl$foreign       <- as.numeric(sl$foreign)-1

## Not run: 
fit1 <- TSVC(participation~income+age, data=sl, family=binomial(link="logit"), 
             nperm=1000, trace=TRUE)
plot(fit1, "income")

fit2 <- TSVC(participation~income+age, data=sl, family=binomial(link="logit"), 
perm_test=FALSE, test_linear=FALSE, splits_max=3)
set.seed(20012025)
ci2  <- confint(fit2, bootstrap_n=500, alpha=0.05, trace=TRUE)
plot(fit2, variable="income", confint=ci2, ellipse_y=0, draw_numbers=FALSE)

## End(Not run)

TSVC documentation built on April 3, 2025, 10:26 p.m.