Running examples in 'dtwclust-Ex.R' failed
The error most likely occurred in:

> ### Name: compare_clusterings
> ### Title: Compare different clustering configurations
> ### Aliases: compare_clusterings
> 
> ### ** Examples
> 
> # Fuzzy preprocessing: calculate autocorrelation up to 50th lag
> acf_fun <- function(series, ...) {
+     lapply(series, function(x) {
+         as.numeric(acf(x, lag.max = 50, plot = FALSE)$acf)
+     })
+ }
> 
> # Define overall configuration
> cfgs <- compare_clusterings_configs(
+     types = c("p", "h", "f", "t"),
+     k = 19L:20L,
+     controls = list(
+         partitional = partitional_control(
+             iter.max = 30L,
+             nrep = 1L
+         ),
+         hierarchical = hierarchical_control(
+             method = "all"
+         ),
+         fuzzy = fuzzy_control(
+             # notice the vector
+             fuzziness = c(2, 2.5),
+             iter.max = 30L
+         ),
+         tadpole = tadpole_control(
+             # notice the vectors
+             dc = c(1.5, 2),
+             window.size = 19L:20L
+         )
+     ),
+     preprocs = pdc_configs(
+         type = "preproc",
+         # shared
+         none = list(),
+         zscore = list(center = c(FALSE)),
+         # only for fuzzy
+         fuzzy = list(
+             acf_fun = list()
+         ),
+         # only for tadpole
+         tadpole = list(
+             reinterpolate = list(new.length = 205L)
+         ),
+         # specify which should consider the shared ones
+         share.config = c("p", "h")
+     ),
+     distances = pdc_configs(
+         type = "distance",
+         sbd = list(),
+         fuzzy = list(
+             L2 = list()
+         ),
+         share.config = c("p", "h")
+     ),
+     centroids = pdc_configs(
+         type = "centroid",
+         partitional = list(
+             pam = list()
+         ),
+         # special name 'default'
+         hierarchical = list(
+             default = list()
+         ),
+         fuzzy = list(
+             fcmdd = list()
+         ),
+         tadpole = list(
+             default = list(),
+             shape_extraction = list(znorm = TRUE)
+         )
+     )
+ )
> 
> # Number of configurations is returned as attribute
> num_configs <- sapply(cfgs, attr, which = "num.configs")
> cat("\nTotal number of configurations without considering optimizations:",
+     sum(num_configs),
+     "\n\n")

Total number of configurations without considering optimizations: 56 

> 
> # Define evaluation functions based on CVI: Variation of Information (only crisp partition)
> vi_evaluators <- cvi_evaluators("VI", ground.truth = CharTrajLabels)
Some of the chosen CVIs are to be minized, but their values will be inverted by the scoring function. See this function's documentation for more details, and use suppressMessages to avoid this message.
> score_fun <- vi_evaluators$score
> pick_fun <- vi_evaluators$pick
> 
> # ====================================================================================
> # Short run with only fuzzy clustering
> # ====================================================================================
> 
> comparison_short <- compare_clusterings(CharTraj, types = c("f"), configs = cfgs,
+                                         seed = 293L, trace = TRUE,
+                                         score.clus = score_fun, pick.clus = pick_fun,
+                                         return.objects = TRUE)
=================================== Preprocessing series ===================================

-------------- Applying fuzzy preprocessings: --------------
  preproc
1 acf_fun

=================================== Performing fuzzy clusterings ===================================

-------------- Using configuration: --------------
       k fuzziness iter.max delta symmetric version preproc distance centroid
1 19, 20         2       30 0.001     FALSE       2 acf_fun       L2    fcmdd

	Precomputing distance matrix...

-------------- Using configuration: --------------
       k fuzziness iter.max delta symmetric version preproc distance centroid
2 19, 20       2.5       30 0.001     FALSE       2 acf_fun       L2    fcmdd

	Precomputing distance matrix...

Error in { : task 1 failed - ""crossprod" is not a BUILTIN function"
Calls: compare_clusterings -> Map -> mapply -> <Anonymous> -> %op%
Execution halted