Runs PC (rank) algorithm given a dataset dat
.
pc_rank_search(dat, alpha = 0.05)
Numeric matrix. Dataset matrix with n
rows (observations) and p
columns (variables).
Numeric --- between 0 and 1. The significance level for the individual conditional independence tests. By default it is set to 0.05.
Square binary matrix (or NA
in case of error).
The CPDAG estimated from the data.
The PC (rank) algorithm has been proposed by Harris, N., and Drton, M., http://jmlr.csail.mit.edu/papers/volume14/harris13a/harris13a.pdf
The function pcalg:pc()
is called with the following
arguments:
suffStat = list(C = 2 * sin(cor(dat, method = "spearman")
* pi/6), n = nrow(dat))
,
indepTest = gaussCItest
,
u2pd = "retry"
--- this ensures that the produced CPDAG
is extendible to a DAG,
skel.method = "stable"
.