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

In dbnR: Dynamic Bayesian Network Learning and Inference

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

a "dbn" S3 object with the structure of the network

Examples

data("motor")
net <- learn_dbn_struc(motor, size = 3)

dbnR documentation built on June 22, 2024, 10:54 a.m.