exact_inference

data.table object with the TS data

size

obj_vars

starting point in the data set to forecast.

Given a bn.fit object, the size of the net and a data.set,
performs exact forecasting over the initial evidence taken from the data set.

Learning and inference over dynamic Bayesian networks of arbitrary
Markovian order. Extends some of the functionality offered by the 'bnlearn'
package to learn the networks from data and perform exact inference.
It offers a modification of Trabelsi (2013) <doi:10.1007/978-3-642-41398-8_34>
dynamic max-min hill climbing algorithm for structure learning and
the possibility to perform forecasts of arbitrary length. A tool for
visualizing the structure of the net is also provided via the 'visNetwork' package.

exact_inference: Performs exact inference forecasting with the GDBN over a data set

Description

Usage

Arguments

Value