$<-.dbn.fit             Replacement function for parameters inside DBNs
AIC.dbn                 Calculate the AIC of a dynamic Bayesian network
AIC.dbn.fit             Calculate the AIC of a dynamic Bayesian network
BIC.dbn                 Calculate the BIC of a dynamic Bayesian network
BIC.dbn.fit             Calculate the BIC of a dynamic Bayesian network
[[<-.dbn.fit            Replacement function for parameters inside DBNs
all.equal.dbn           Check if two network structures are equal to
                        each other
all.equal.dbn.fit       Check if two fitted networks are equal to each
                        other
as.character.dbn        Convert a network structure into a model string
calc_mu                 Calculate the mu vector from a fitted BN or DBN
calc_sigma              Calculate the sigma covariance matrix from a
                        fitted BN or DBN
coef.dbn.fit            Extracts the coefficients of a DBN
degree                  Calculates the degree of a list of nodes
filter_same_cycle       Filter the instances in a data.table with
                        different ids in each row
filtered_fold_dt        Fold a dataset avoiding overlapping of
                        different time series
fit_dbn_params          Fits a markovian n DBN model
fitted.dbn.fit          Extracts the fitted values of a DBN
fold_dt                 Widens the dataset to take into account the t
                        previous time slices
forecast_ts             Performs forecasting with the GDBN over a
                        dataset
generate_random_network_exp
                        Generate a random DBN and a sampled dataset
learn_dbn_struc         Learns the structure of a markovian n DBN model
                        from data
logLik.dbn              Calculate the log-likelihood of a dynamic
                        Bayesian network
logLik.dbn.fit          Calculate the log-likelihood of a dynamic
                        Bayesian network
mean.dbn.fit            Average the parameters of multiple dbn.fit
                        objects with identical structures
motor                   Multivariate time series dataset on the
                        temperature of an electric motor
mvn_inference           Performs inference over a multivariate normal
                        distribution
nodes                   Returns a list with the names of the nodes of a
                        BN or a DBN
nodes<-                 Relabel the names of the nodes of a BN or a DBN
plot.dbn                Plots a dynamic Bayesian network
plot.dbn.fit            Plots a fitted dynamic Bayesian network
plot_dynamic_network    Plots a dynamic Bayesian network in a
                        hierarchical way
plot_static_network     Plots a Bayesian network in a hierarchical way
predict.dbn.fit         Performs inference in every row of a dataset
                        with a DBN
predict_bn              Performs inference over a fitted GBN
predict_dt              Performs inference over a test dataset with a
                        GBN
print.dbn               Print method for "dbn" objects
print.dbn.fit           Print method for "dbn.fit" objects
rbn.dbn.fit             Simulates random samples from a fitted DBN
reduce_freq             Reduce the frequency of the time series data in
                        a data.table
residuals.dbn.fit       Returns the residuals from fitting a DBN
score                   Computes the score of a BN or a DBN
shift_values            Move the window of values backwards in a folded
                        dataset row
sigma.dbn.fit           Returns the standard deviation of the residuals
                        from fitting a DBN
smooth_ts               Performs smoothing with the GDBN over a dataset
time_rename             Renames the columns in a data.table so that
                        they end in '_t_0'
