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

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: NetworkMotif
> ### Title: Estimating the uncertainty of a specified network
> ### Aliases: NetworkMotif
> 
> ### ** Examples
> 
> 
> 
> #' # ---------------------------------------------------------
> 
> # Example 1:
> # Run NetworkMotif to do uncertainty quantification for a given network among the response variable
> 
> # Data Generation
> set.seed(9154)
> 
> # Number of data points
> n = 10000
> 
> # Number of response variables and number of instrument variables
> p = 3
> k = 4
> 
> # Initialize causal interaction matrix between response variables
> A = matrix(sample(c(-0.1, 0.1), p^2, replace = TRUE), p, p)
> 
> # Diagonal entries of A matrix will always be 0
> diag(A) = 0
> 
> # Make the network sparse
> A[sample(which(A!=0), length(which(A!=0))/2)] = 0
> 
> # Initialize causal interaction matrix between response and instrument variables
> B = matrix(0, p, k)
> 
> # Create d vector
> d = c(2, 1, 1)
> 
> 
> # Initialize m
> m = 1
> 
> # Calculate B matrix based on d vector
> for (i in 1:p) {
+ 
+  # Update ith row of B
+  B[i, m:(m + d[i] - 1)] = 1
+ 
+  # Update m
+  m = m + d[i]
+ 
+ }
> 
> Sigma = diag(p)
> 
> Mult_Mat = solve(diag(p) - A)
> 
> Variance = Mult_Mat %*% Sigma %*% t(Mult_Mat)
> 
> # Generate instrument data matrix
> X = matrix(rnorm(n * k, 0, 1), nrow = n, ncol = k)
> 
> # Initialize response data matrix
> Y = matrix(0, nrow = n, ncol = p)
> 
> # Generate response data matrix based on instrument data matrix
> for (i in 1:n) {
+ 
+     Y[i, ] = MASS::mvrnorm(n = 1, Mult_Mat %*% B %*% X[i, ], Variance)
+ 
+ }
> 
> 
> # Apply RGM on individual level data for Threshold Prior
> Output = RGM(X = X, Y = Y, d = c(2, 1, 1), prior = "Threshold")
> 
> # Store Gamma_Pst
> Gamma_Pst = Output$Gamma_Pst
> 
> # Define a function to create smaller arrowheads
> smaller_arrowheads = function(graph) {
+     igraph::E(graph)$arrow.size = 1  # Adjust the arrow size value as needed
+     return(graph)
+ }
> 
> # Start with a random subgraph
> Gamma = matrix(0, nrow = p, ncol = p)
> Gamma[2, 1] = 1
> 
> # Plot the subgraph to get an idea about the causal network
> plot(smaller_arrowheads(igraph::graph.adjacency(Gamma,
+          mode = "directed")), layout = igraph::layout_in_circle,
+             main = "Subgraph")
Error in loadNamespace(x) : there is no package called ‘igraph’
Calls: plot ... loadNamespace -> withRestarts -> withOneRestart -> doWithOneRestart
Execution halted