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

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: xyplot.cv
> ### Title: X-Y plots of cross-validation results
> ### Aliases: xyplot.cv xyplot.cvSelect xyplot.cvTuning
> ### Keywords: hplot
> 
> ### ** Examples
> 
> library("robustbase")
> data("coleman")
> set.seed(1234)  # set seed for reproducibility
> 
> ## set up folds for cross-validation
> folds <- cvFolds(nrow(coleman), K = 5, R = 10)
> 
> 
> ## compare LS, MM and LTS regression
> 
> # perform cross-validation for an LS regression model
> fitLm <- lm(Y ~ ., data = coleman)
> cvFitLm <- cvLm(fitLm, cost = rtmspe, 
+     folds = folds, trim = 0.1)
> 
> # perform cross-validation for an MM regression model
> fitLmrob <- lmrob(Y ~ ., data = coleman, k.max = 500)
> cvFitLmrob <- cvLmrob(fitLmrob, cost = rtmspe, 
+     folds = folds, trim = 0.1)
Warning in lmrob.S(x, y, control = control) :
  find_scale() did not converge in 'maxit.scale' (= 200) iterations with tol=1e-10, last rel.diff=0
Warning in lmrob.S(x, y, control = control) :
  find_scale() did not converge in 'maxit.scale' (= 200) iterations with tol=1e-10, last rel.diff=0
Warning in lmrob.S(x, y, control = control) :
  find_scale() did not converge in 'maxit.scale' (= 200) iterations with tol=1e-10, last rel.diff=0
> 
> # perform cross-validation for an LTS regression model
> fitLts <- ltsReg(Y ~ ., data = coleman)
> cvFitLts <- cvLts(fitLts, cost = rtmspe, 
+     folds = folds, trim = 0.1)
> 
> # combine and plot results
> cvFits <- cvSelect(LS = cvFitLm, MM = cvFitLmrob, LTS = cvFitLts)
> cvFits

5-fold CV results:
  Fit       CV
1  LS 1.775811
2  MM 1.023272
3 LTS 1.165749

Best model:
  CV 
"MM" 
> xyplot(cvFits)
> 
> 
> ## compare raw and reweighted LTS estimators for 
> ## 50% and 75% subsets
> 
> # 50% subsets
> fitLts50 <- ltsReg(Y ~ ., data = coleman, alpha = 0.5)
> cvFitLts50 <- cvLts(fitLts50, cost = rtmspe, folds = folds, 
+     fit = "both", trim = 0.1)
> 
> # 75% subsets
> fitLts75 <- ltsReg(Y ~ ., data = coleman, alpha = 0.75)
> cvFitLts75 <- cvLts(fitLts75, cost = rtmspe, folds = folds, 
+     fit = "both", trim = 0.1)
> 
> # combine and plot results
> cvFitsLts <- cvSelect("0.5" = cvFitLts50, "0.75" = cvFitLts75)
> cvFitsLts

5-fold CV results:
   Fit reweighted      raw
1  0.5   1.165749 1.528544
2 0.75   1.011054 1.167683

Best model:
reweighted        raw 
    "0.75"     "0.75" 
> xyplot(cvFitsLts)
> 
> 
> ## evaluate MM regression models tuned for 
> ## 80%, 85%, 90% and 95% efficiency
> tuning <- list(tuning.psi=c(3.14, 3.44, 3.88, 4.68))
> 
> # perform cross-validation
> cvFitsLmrob <- cvTuning(fitLmrob$call, data = coleman, 
+     y = coleman$Y, tuning = tuning, cost = rtmspe, 
+     folds = folds, costArgs = list(trim = 0.1))
Warning in lmrob.S(x, y, control = control) :
  find_scale() did not converge in 'maxit.scale' (= 200) iterations with tol=1e-10, last rel.diff=0
Warning in lmrob.S(x, y, control = control) :
  find_scale() did not converge in 'maxit.scale' (= 200) iterations with tol=1e-10, last rel.diff=0
Warning in lmrob.S(x, y, control = control) :
  find_scale() did not converge in 'maxit.scale' (= 200) iterations with tol=1e-10, last rel.diff=0
Warning in lmrob.S(x, y, control = control) :
  find_scale() did not converge in 'maxit.scale' (= 200) iterations with tol=1e-10, last rel.diff=0
Warning in lmrob.S(x, y, control = control) :
  find_scale() did not converge in 'maxit.scale' (= 200) iterations with tol=1e-10, last rel.diff=0
Warning in lmrob.S(x, y, control = control) :
  find_scale() did not converge in 'maxit.scale' (= 200) iterations with tol=1e-10, last rel.diff=0
Warning in lmrob.S(x, y, control = control) :
  find_scale() did not converge in 'maxit.scale' (= 200) iterations with tol=1e-10, last rel.diff=0
Warning in lmrob.S(x, y, control = control) :
  find_scale() did not converge in 'maxit.scale' (= 200) iterations with tol=1e-10, last rel.diff=0
Warning in lmrob.S(x, y, control = control) :
  find_scale() did not converge in 'maxit.scale' (= 200) iterations with tol=1e-10, last rel.diff=0
Warning in lmrob.S(x, y, control = control) :
  find_scale() did not converge in 'maxit.scale' (= 200) iterations with tol=1e-10, last rel.diff=0
Warning in lmrob.S(x, y, control = control) :
  find_scale() did not converge in 'maxit.scale' (= 200) iterations with tol=1e-10, last rel.diff=0
Warning in lmrob.S(x, y, control = control) :
  find_scale() did not converge in 'maxit.scale' (= 200) iterations with tol=1e-10, last rel.diff=0
Warning in lmrob.S(x, y, control = control) :
  find_scale() did not converge in 'maxit.scale' (= 200) iterations with tol=1e-10, last rel.diff=0
Warning in lmrob.S(x, y, control = control) :
  find_scale() did not converge in 'maxit.scale' (= 200) iterations with tol=1e-10, last rel.diff=0
Warning in lmrob.S(x, y, control = control) :
  find_scale() did not converge in 'maxit.scale' (= 200) iterations with tol=1e-10, last rel.diff=0
Warning in lmrob.S(x, y, control = control) :
  find_scale() did not converge in 'maxit.scale' (= 200) iterations with tol=1e-10, last rel.diff=0
> cvFitsLmrob

5-fold CV results:
  tuning.psi       CV
1       3.14 1.037657
2       3.44 1.031808
3       3.88 1.030184
4       4.68 1.023149

Optimal tuning parameter:
   tuning.psi
CV       4.68
> 
> # plot results
> xyplot(cvFitsLmrob)
> 
> 
> 
> base::assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv")
> base::cat("xyplot.cv", base::get(".format_ptime", pos = 'CheckExEnv')(get(".dptime", pos = "CheckExEnv")), "\n", file=base::get(".ExTimings", pos = 'CheckExEnv'), append=TRUE, sep="\t")
> ### * <FOOTER>
> ###
> cleanEx()
> options(digits = 7L)
> base::cat("Time elapsed: ", proc.time() - base::get("ptime", pos = 'CheckExEnv'),"\n")
Time elapsed:  79.453 0.305 93.327 0 0 
> grDevices::dev.off()
null device 
          1 
> ###
> ### Local variables: ***
> ### mode: outline-minor ***
> ### outline-regexp: "\\(> \\)?### [*]+" ***
> ### End: ***
> quit('no')
Assertion failure at kmp_runtime.cpp(6918): temp_reg_status_file_name.
OMP: Error #13: Assertion failure at kmp_runtime.cpp(6918).
OMP: Hint Please submit a bug report with this message, compile and run commands used, and machine configuration info including native compiler and operating system versions. Faster response will be obtained by including all program sources. For information on submitting this issue, please see https://bugs.llvm.org/.
Assertion failure at kmp_runtime.cpp(6918): temp_reg_status_file_name.
OMP: Error #13: Assertion failure at kmp_runtime.cpp(6918).
OMP: Hint Please submit a bug report with this message, compile and run commands used, and machine configuration info including native compiler and operating system versions. Faster response will be obtained by including all program sources. For information on submitting this issue, please see https://bugs.llvm.org/.
Killed