R Under development (unstable) (2025-04-16 r88149 ucrt) -- "Unsuffered Consequences"
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> stopifnot(require(hdi))
Loading required package: hdi
Loading required package: scalreg
Loading required package: lars
Loaded lars 1.3

> 
> ## this is the example code of the help file of plotClusterGroupBound
> 
> 
> ## Create a regression problem with correlated design (n = 10, p = 3):
> ## a block of size 2 and a block of size 1, within-block correlation is 0.99
> 
> set.seed(29)
> p   <- 3
> n   <- 10
> 
> Sigma <- diag(p)
> Sigma[1,2] <- Sigma[2,1] <- 0.99
> 
> x <- matrix(rnorm(n * p), nrow = n) %*% chol(Sigma)
> 
> ## Create response with active variable 1
> beta    <- rep(0, p)
> beta[1] <- 5
> 
> y  <- as.numeric(x %*% beta + rnorm(n))
> 
> ## Compute the lower bound for all groups in a hierarchical clustering tree
> cgb5 <- clusterGroupBound(x, y, nsplit = 4) ## use larger value for nsplit!

  5    3 member(s)	 with lower bound 3.642297
  3    1 member(s)	 with lower bound 0

  4    2 member(s)	 with lower bound 3.057924
  1    1 member(s)	 with lower bound 0

  2    1 member(s)	 with lower bound 0


> 
> ## Plot the tree with y-axis proportional to the (log) of the number of
> ## group members and node sizes proportional to the lower l1-norm bound.
> plot(cgb5)
> 
> ## Show the lower bound on the y-axis and node sizes proportional to
> ## number of group members
> plot(cgb5, yaxis = "")
> 
> proc.time()
   user  system elapsed 
   4.15    4.64    8.81