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Structure learning for Bayesian networks using the CCDr algorithm.
dat <- data.frame(x = runif(3), y = c("a", "d", "c"))
apply(dat, 2, class)
returns
x y
"character" "character"
Should probably use unlist(lapply(dat, class))
instead.
The function cor_vector_ivn
belongs in sparsebnUtils (see also cor_vector
therein). Might consider turning this into an S3 method for sparsebnData
objects.
If a user specifies ivn.rand=FALSE
in generate_mvn_data
, but forgets to include the intervention values in the ivn
argument, this should be an error. Currently, the function returns incorrect output.
The problem is this line, which returns NULL
if ivn
is not properly set. There should be more careful checks for the ivn.rand
argument to prevent this situation.
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