View source: R/structure_learning_dmmhc.R
dmmhc | R Documentation |
Learns a gaussian dynamic Bayesian network from a dataset. It allows the creation of markovian n nets rather than only markov 1.
dmmhc( dt, size = 2, f_dt = NULL, blacklist = NULL, intra = TRUE, blacklist_tr = NULL, ... )
dt |
the data.frame or data.table to be used |
size |
number of time slices of the net. Markovian 1 would be size 2 |
f_dt |
previously folded dataset, in case some specific rows have to be removed after the folding |
blacklist |
an optional matrix indicating forbidden arcs between nodes |
intra |
if TRUE, the intra-slice arcs of the network will be learnt. If FALSE, they will be ignored |
blacklist_tr |
an optional matrix indicating forbidden intra-slice arcs between nodes |
... |
additional parameters for |
the structure of the net
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