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

> ### Name: getParents
> ### Title: Estimate the connectivity matrix of a causal graph
> ### Aliases: getParents
> ### Keywords: Causality, Graph estimations
> 
> ### ** Examples
> 
> ## load the backShift package for data generation and plotting functionality
> if(!requireNamespace("backShift", quietly = TRUE))
+  stop("The package 'backShift' is needed for the examples to
+  work. Please install it.", call. = FALSE)
> 
> require(backShift)
Loading required package: backShift
> 
> # Simulate data with connectivity matrix A with assumptions
> # 1) hidden variables present
> # 2) precise location of interventions is assumed unknown
> # 3) different environments can be distinguished
> 
> ## simulate data
> myseed <- 1
> 
> # sample size n
> n <- 10000
> 
> # p=3 predictor variables and connectivity matrix A
> p <- 3
> labels <- c("1", "2", "3")
> A <- diag(p)*0
> A[1,2] <- 0.8
> A[2,3] <- 0.8
> A[3,1] <- -0.4
> 
> # divide data in 10 different environments
> G <- 10
> 
> # simulate
> simResult <- simulateInterventions(n, p, A, G, intervMultiplier = 3,
+              noiseMult = 1, nonGauss = TRUE, hiddenVars = TRUE,
+              knownInterventions = FALSE, fracVarInt = NULL, simulateObs = TRUE,
+              seed = myseed)
> X <- simResult$X
> environment <- simResult$environment
> 
> ## apply all  methods given in vector 'methods'
> ## (using all data pooled for pc/LINGAM/rfci/ges -- can be changed with option
> ## 'onlyObservationalData=TRUE')
> 
> methods <- c("backShift", "LINGAM") #c("pc", "rfci", "ges")
> 
> # select whether you want to run stability selection
> stability <- FALSE
> 
> # arrange graphical output into a rectangular grid
> sq <- ceiling(sqrt(length(methods)+1))
> par(mfrow=c(ceiling((length(methods)+1)/sq),sq))
> 
> ## plot and print true graph
> cat("\n true graph is  ------  \n" )

 true graph is  ------  
> print(A)
     [,1] [,2] [,3]
[1,]  0.0  0.8  0.0
[2,]  0.0  0.0  0.8
[3,] -0.4  0.0  0.0
> plotGraphEdgeAttr(A, plotStabSelec = FALSE, labels = labels, thres.point = 0,
+  main = "TRUE GRAPH")
> 
> ## loop over all methods and compute and print/plot estimate
> for (method in methods){
+   cat("\n result for method", method,"  ------  \n" )
+ 
+   if(!stability){
+     # Option 1): use this estimator as a point estimate
+     Ahat <- getParents(X, environment, method=method, alpha=0.1, pointConf = TRUE)
+   }else{
+     # Option 2): use a stability selection based estimator
+     # with expected number of false positives bounded by EV=2
+     Ahat <- getParentsStable(X, environment, EV=2, method=method, alpha=0.1)
+   }
+ 
+   # print and plot estimate (point estimate thresholded if numerical estimates
+   # are returned)
+   print(Ahat)
+   if(!stability)
+     plotGraphEdgeAttr(Ahat, plotStabSelec = FALSE, labels = labels,
+      thres.point = 0.05,
+      main=paste("POINT ESTIMATE FOR METHOD\n", toupper(method)))
+   else
+     plotGraphEdgeAttr(Ahat, plotStabSelec = TRUE, labels = labels,
+      thres.point = 0, main = paste("STABILITY SELECTION
+      ESTIMATE\n FOR METHOD", toupper(method)))
+  }

 result for method backShift   ------  
3 x 3 sparse Matrix of class "dgCMatrix"
           1            2           3
1  .          0.802217975 -0.05583784
2  0.0047767  .            0.78766266
3 -0.4062989 -0.006501869  .         

 result for method LINGAM   ------  
Error: The package 'pcalg' is needed for LINGAM to 
work. Please install it.
Execution halted