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

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: teigen
> ### Title: teigen: Function for Model-Based Clustering and Classification
> ###   with the Multivariate t Distribution
> ### Aliases: teigen
> 
> ### ** Examples
> 
> ###Note that only one model is run for each example
> ###in order to reduce computation time
> 
> #Clustering old faithful data with hard random start
> tfaith <- teigen(faithful, models="UUUU", Gs=1:3, init="hard")
Time taken:???  |  Approx. remaining:???  |  0% completeTime taken:   0.2 secs  |  Approx. remaining:   0.3 secs  |    33% completeTime taken:   0.2 secs  |  Approx. remaining:   0.1 secs  |    67% completeTime taken:   0.2 secs  |  Approx. remaining:     0 secs  |   100% complete
> plot(tfaith, what = "uncertainty")
> summary(tfaith)
------------- Summary for teigen ------------- 
            ------   RESULTS   ------     
            Loglik:         -384.389 
            BIC:            -841.6535 
            ICL:            -842.3337 
            Model:          UUUU 
            # Groups:       2 


Clustering Table:   

  1   2 
 97 175 
> 
> #Clustering old faithful with hierarchical starting values
> initial_list <- list()
> clustree <- hclust(dist(faithful))
> for(i in 1:3){
+ 	initial_list[[i]] <- cutree(clustree,i)
+ }
> tfaith <- teigen(faithful, models="CUCU", Gs=1:3, init=initial_list)
Time taken:???  |  Approx. remaining:???  |  0% completeTime taken:   0.4 secs  |  Approx. remaining:   0.8 secs  |    33% completeTime taken:   0.4 secs  |  Approx. remaining:   0.2 secs  |    67% completeTime taken:   0.5 secs  |  Approx. remaining:     0 secs  |   100% complete
> print(tfaith)
BIC and ICL select the same model and groups.
The best model (BIC of -844.52, ICL of -845.1251) is CUCU with G=2
> 
> #Classification with the iris data set
> #Introducing NAs is not required; this is to illustrate a `true' classification scenario
> irisknown <- iris[,5]
> irisknown[134:150] <- NA
> triris <- teigen(iris[,-5], models="CUUU", init="uniform", known=irisknown)
Time taken:???  |  Approx. remaining:???  |  0% completeTime taken:   0.1 secs  |  Approx. remaining:     0 secs  |   100% complete
> 
> ##Parallel examples:
> ###Note: parallel.cores set to 2 in order to comply
> ###with CRAN submission policies (set to higher
> ###number or TRUE to automatically use all available cores)
> 
> #Clustering old faithful data with tEIGEN
> tfaith <- teigen(faithful, models="UUUU",
+ parallel.cores=2, Gs=1:3, init="hard")
> plot(tfaith, what = "contour")
> 
> #Classification with the iris data set 
> irisknown <- iris[,5]
> irisknown[sample(1:nrow(iris),50)] <- NA
> tiris <- teigen(iris[,-5], parallel.cores=2, models="CUUU",
+ init="uniform", known=irisknown)
Error in serverSocket(port = port) : 
  creation of server socket failed: port 11687 cannot be opened
Calls: teigen ... <Anonymous> -> makeCluster -> makePSOCKcluster -> serverSocket
Execution halted