AncReg (version 1.0.1)

instant_graph: Instantaneous graph

Description

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

Usage

instant_graph(lin.anc, alpha = 0.05, verbose = FALSE, corr = TRUE)

Value

A list containing:

rec.ancs

A boolean matrix indicating whether one variable affects another instantaneously

alpha

The significance level to avoid cycles

Arguments

lin.anc

output from AncReg()

alpha

significance level

verbose

should information be printed?

corr

should multiplicity correction be applied?

See Also

AncReg, instant_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 instantaneous graph
instant_graph(fit, alpha = 0.01, verbose = TRUE)