exact_inference_backwards

data.table object with the TS data

size

variables to be predicted. Should be in the oldest time step

obj_vars

starting point in the data set to smooth

variables to be provided as evidence in each forecasting step. Should be in the oldest time step

prov_ev

Given a bn.fit object, the size of the net and a data.set,
performs exact smoothing over the initial evidence taken from the data set.
Take notice that the smoothing is done backwards in time, as opposed to
forecasting.

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 three structure learning algorithms for dynamic Bayesian networks
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_backwards: Performs exact inference smoothing with the GDBN over a data set

Description

Usage

Arguments

Value