Dynamic Bayesian Network Learning and Inference

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Documentation for package ‘dbnR’ version 0.7.9

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$<-.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
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
BIC.dbn Calculate the BIC of a dynamic Bayesian network
BIC.dbn.fit Calculate the BIC of a dynamic Bayesian network
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
filtered_fold_dt Fold a dataset avoiding overlapping of different time series
filter_same_cycle Filter the instances in a data.table with different ids in each row
fitted.dbn.fit Extracts the fitted values of a DBN
fit_dbn_params Fits a markovian n DBN model
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'
[[<-.dbn.fit Replacement function for parameters inside DBNs