dbnR (version 0.7.1)

learn_dbn_struc: Learns the structure of a markovian n DBN model from data

Description

Learns a gaussian dynamic Bayesian network from a dataset. It allows the creation of markovian n nets rather than only markov 1.

Usage

learn_dbn_struc(dt, size = 2, method = "dmmhc", f_dt = NULL, ...)

Arguments

dt

the data.frame or data.table to be used

size

number of time slices of the net. Markovian 1 would be size 2

method

the structure learning method of choice to use

f_dt

previously folded dataset, in case some specific rows have to be removed after the folding

...

additional parameters for rsmax2 function

Value

the structure of the net

Examples

# NOT RUN {
data("motor")
net <- learn_dbn_struc(motor, size = 3)
# }