Usage
fast.iamb(x, cluster = NULL, whitelist = NULL, blacklist = NULL,
test = "mi", alpha = 0.05, debug = FALSE, optimized = TRUE,
strict = TRUE, direction = FALSE)Arguments
x
a data frame, containing the variables in the model.
whitelist
a data frame with two columns (optionally labeled
"from" and "to"), containing a set of arcs to be included in the
graph.
blacklist
a data frame with two columns (optionally labeled
"from" and "to"), containing a set of arcs not to be included in
the graph.
test
a character string, the label of the conditional
independence test to be used in the algorithm. Possible
values are mi (mutual information), mh
(Cochran-Mantel-Haenszel), fmi (
alpha
a numerical value, the target nominal type I error rate.
debug
a boolean value. If TRUE a lot of debugging output is
printed; otherwise the function is completely silent.
strict
a boolean value. If TRUE conflicting results in the
structure learning generate an error; otherwise they result in
a warning.
direction
a boolean value. If TRUE each possible direction
of each undirected arc is tested, and the one with the lowest
p-value is accepted as the true direction for that arc.