summary_graph: Summary graph

In AncReg: Ancestor Regression

Summary graph

Description

Construct summary graph from p-values and significance level. Recursively constructs all ancestral connections by adding ancestors of ancestors.

Usage

summary_graph(lin.anc, alpha = 0.05, corr = TRUE)

Arguments

lin.anc	output from AncReg()
alpha	significance level
corr	should multiplicity correction be applied?

Value

A boolean matrix indicating whether one variable affects another

See Also

AncReg, summary_p.val

Examples

# random DAGS for simulation
set.seed(1234)

p <- 5 #number of nodes
DAG <- pcalg::randomDAG(p, prob = 0.5)

B <- matrix(0, p, p) # represent DAG as matrix
for (i in 2:p){
  for(j in 1:(i-1)){
    # store edge weights
    B[i,j] <- max(0, DAG@edgeData@data[[paste(j,"|",i, sep="")]]$weight)
  }
}
colnames(B) <- rownames(B) <- LETTERS[1:p]

# solution in terms of noise
Bprime <- MASS::ginv(diag(p) - B)

n <- 500
N <- matrix(rexp(n * p), ncol = p)
X <- t(Bprime %*% t(N))
colnames(X) <- LETTERS[1:p]

# fit ancestor regression
fit <- AncReg(X)

# generate summary graph
summary_graph(fit, alpha = 0.1)

AncReg documentation built on Aug. 8, 2025, 7:48 p.m.