Running examples in ‘party-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: mob
> ### Title: Model-based Recursive Partitioning
> ### Aliases: mob mob-class coef.mob deviance.mob fitted.mob logLik.mob
> ###   predict.mob print.mob residuals.mob sctest.mob summary.mob
> ###   weights.mob
> ### Keywords: tree
> 
> ### ** Examples
> 
> 
> set.seed(290875)
> 
> if(require("mlbench")) {
+ 
+ ## recursive partitioning of a linear regression model
+ ## load data
+ data("BostonHousing", package = "mlbench")
+ ## and transform variables appropriately (for a linear regression)
+ BostonHousing$lstat <- log(BostonHousing$lstat)
+ BostonHousing$rm <- BostonHousing$rm^2
+ ## as well as partitioning variables (for fluctuation testing)
+ BostonHousing$chas <- factor(BostonHousing$chas, levels = 0:1, 
+                              labels = c("no", "yes"))
+ BostonHousing$rad <- factor(BostonHousing$rad, ordered = TRUE)
+ 
+ ## partition the linear regression model medv ~ lstat + rm
+ ## with respect to all remaining variables:
+ fmBH <- mob(medv ~ lstat + rm | zn + indus + chas + nox + age + 
+                                 dis + rad + tax + crim + b + ptratio,
+   control = mob_control(minsplit = 40), data = BostonHousing, 
+   model = linearModel)
+ 
+ ## print the resulting tree
+ fmBH
+ ## or better visualize it
+ plot(fmBH)
+ 
+ ## extract coefficients in all terminal nodes
+ coef(fmBH)
+ ## look at full summary, e.g., for node 7
+ summary(fmBH, node = 7)
+ ## results of parameter stability tests for that node
+ sctest(fmBH, node = 7)
+ ## -> no further significant instabilities (at 5% level)
+ 
+ ## compute mean squared error (on training data)
+ mean((BostonHousing$medv - fitted(fmBH))^2)
+ mean(residuals(fmBH)^2)
+ deviance(fmBH)/sum(weights(fmBH))
+ 
+ ## evaluate logLik and AIC
+ logLik(fmBH)
+ AIC(fmBH)
+ ## (Note that this penalizes estimation of error variances, which
+ ## were treated as nuisance parameters in the fitting process.)
+ 
+ 
+ ## recursive partitioning of a logistic regression model
+ ## load data
+ data("PimaIndiansDiabetes", package = "mlbench")
+ ## partition logistic regression diabetes ~ glucose 
+ ## wth respect to all remaining variables
+ fmPID <- mob(diabetes ~ glucose | pregnant + pressure + triceps + 
+                                   insulin + mass + pedigree + age,
+   data = PimaIndiansDiabetes, model = glinearModel, 
+   family = binomial())
+ 
+ ## fitted model
+ coef(fmPID)
+ plot(fmPID)
+ plot(fmPID, tp_args = list(cdplot = TRUE))
+ }
Loading required package: mlbench
Error in terminal_panel(<S4 object of class "mob">) : 
  the `vcd' package is required for CD plots
Calls: plot ... plot.mob -> plot.BinaryTree -> do.call -> terminal_panel
Execution halted