acc_successions         Returns a vector with the number of consecutive
                        nodes in each level
add_attr_to_fit         Adds the mu vector and sigma matrix as
                        attributes to the bn.fit or dbn.fit object
approx_prediction_step
                        Performs approximate inference in a time slice
                        of the dbn
approximate_inference   Performs approximate inference forecasting with
                        the GDBN over a data set
calc_mu                 Calculate the mu vector of means of a Gaussian
                        linear network. Front end of a C++ function.
calc_mu_cpp             Calculate the mu vector of means of a Gaussian
                        linear network. This is the C++ backend of the
                        function.
calc_sigma              Calculate the sigma covariance matrix of a
                        Gaussian linear network. Front end of a C++
                        function.
calc_sigma_cpp          Calculate the sigma covariance matrix of a
                        Gaussian linear network. This is the C++
                        backend of the function.
check_time0_formatted   Checks if the vector of names are time
                        formatted to t0
create_blacklist        Creates the blacklist of arcs from a folded
                        data.table
dynamic_ordering        Gets the ordering of a single time slice in a
                        DBN
exact_inference         Performs exact inference forecasting with the
                        GDBN over a data set
exact_prediction_step   Performs exact inference in a time slice of the
                        dbn
expand_time_nodes       Extends the names of the nodes in t_0 to
                        t_(max-1)
fit_dbn_params          Fits a markovian n DBN model
fold_dt                 Widens the dataset to take into account the t
                        previous time slices
fold_dt_rec             Widens the dataset to take into account the t
                        previous time slices
forecast_ts             Performs forecasting with the GDBN over a data
                        set
learn_dbn_struc         Learns the structure of a markovian n DBN model
                        from data
merge_nets              Merges and replicates the arcs in the static BN
                        into all the time-slices in the DBN
motor                   Multivariate time series dataset on the
                        temperature of an electric motor
mvn_inference           Performs inference over a multivariate normal
                        distribution
node_levels             Defines a level for every node in the net
plot_dynamic_network    Plots a dynamic Bayesian network in a
                        hierarchical way
plot_network            Plots a Bayesian networks in a hierarchical way
predict_bn              Performs inference over a fitted GBN
predict_dt              Performs inference over a test data set with a
                        GBN
time_rename             Renames the columns in a data.table so that
                        they end in '_t_0'
