Dynamic Bayesian Network Learning and Inference

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Documentation for package ‘dbnR’ version 0.4.5

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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
approximate_inference Performs approximate inference forecasting with the GDBN over a data set
approx_prediction_step Performs approximate inference in a time slice of the dbn
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'