Usage
pcAlgo(dm = NA, C = NA, n=NA, alpha, corMethod = "standard",
verbose=FALSE, directed=FALSE, G=NULL, datatype = "continuous",
NAdelete=TRUE, m.max=Inf, u2pd = "rand", psepset=FALSE)Arguments
dm
Data matrix; rows correspond to samples, cols correspond to
nodes.
C
Correlation matrix; this is an alternative for specifying the
data matrix.
n
Sample size; this is only needed if the data matrix is not
provided.
alpha
Significance level for the individual partial correlation tests.
corMethod
A character string speciyfing the method for
(partial) correlation estimation.
"standard", "QnStable", "Qn" or "ogkQn" for standard and robust (based on
the Qn scale estimator without and with OGK) correlation
estimation. For robust estim
verbose
0-no output, 1-small output, 2-details;using 1 and 2
makes the function very much slower
directed
If FALSE, the underlying skeleton is computed;
if TRUE, the underlying CPDAG is computed
G
The adjacency matrix of the graph from which the algorithm
should start (logical)
datatype
Distinguish between discrete and continuous data
NAdelete
Delete edge if pval=NA (for discrete data)
m.max
Maximal size of conditioning set
u2pd
Function used for converting skeleton to cpdag. "rand"
(use udag2pdag); "relaxed" (use udag2pdagRelaxed); "retry" (use
udag2pdagSpecial)
psepset
If true, also possible separation sets are tested.