Man pages for dkesada/dbnR
Dynamic Bayesian Network Learning and Inference
| acc_successions | Returns a vector with the number of consecutive nodes in each... |
| add_attr_to_fit | Adds the mu vector and sigma matrix as attributes to the... |
| 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 |
| approximate_inference | Performs approximate inference forecasting with the GDBN over... |
| approx_prediction_step | Performs approximate inference in a time slice of the dbn |
| as.character.dbn | Convert a network structure into a model string |
| as_named_vector | Converts a single row data.table into a named vector |
| BIC.dbn | Calculate the BIC of a dynamic Bayesian network |
| BIC.dbn.fit | Calculate the BIC of a dynamic Bayesian network |
| bn_translate_exp | Experimental function that translates a natPosition vector... |
| calc_mu | Calculate the mu vector from a fitted BN or DBN |
| calc_mu_cpp | Calculate the mu vector of means of a Gaussian linear... |
| calc_sigma | Calculate the sigma covariance matrix from a fitted BN or DBN |
| calc_sigma_cpp | Calculate the sigma covariance matrix of a Gaussian linear... |
| cash-set-.dbn.fit | Replacement function for parameters inside DBNs |
| Causlist | R6 class that defines causal lists in the PSO |
| check_time0_formatted | Checks if the vector of names are time formatted to t_0 |
| cl_to_arc_matrix_cpp | Create a matrix with the arcs defined in a causlist object |
| coef.dbn.fit | Extracts the coefficients of a DBN |
| create_blacklist | Creates the blacklist of arcs from a folded data.table |
| create_causlist_cpp | Create a causal list from a DBN. This is the C++ backend of... |
| create_natcauslist_cpp | Create a natural causal list from a DBN. This is the C++... |
| crop_names_cpp | If the names of the nodes have "_t_0" appended at the end,... |
| cte_times_vel_cpp | Multiply a Velocity by a constant real number |
| degree | Calculates the degree of a list of nodes |
| degree.bn | Calculates the degree of a list of nodes |
| degree.bn.fit | Calculates the degree of a list of nodes |
| degree.dbn | Calculates the degree of a list of nodes |
| degree.dbn.fit | Calculates the degree of a list of nodes |
| dmmhc | Learns the structure of a markovian n DBN model from data |
| dynamic_ordering | Gets the ordering of a single time slice in a DBN |
| exact_inference | Performs exact inference forecasting with the GDBN over a... |
| exact_inference_backwards | Performs exact inference smoothing with the GDBN over a... |
| 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) |
| 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... |
| 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... |
| fold_dt_rec | Widens the dataset to take into account the t previous time... |
| forecast_ts | Performs forecasting with the GDBN over a dataset |
| generate_random_network_exp | Generate a random DBN and a sampled dataset |
| init_cl_cpp | Initialize the nodes vector |
| initialize_cl_cpp | Create a causality list and initialize it |
| init_list_cpp | Initialize the particles |
| 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... |
| merge_nets | Merges and replicates the arcs in the static BN into all the... |
| motor | Multivariate time series dataset on the temperature of an... |
| mvn_inference | Performs inference over a multivariate normal distribution |
| natCauslist | R6 class that defines causal lists in the PSO |
| nat_cl_to_arc_matrix_cpp | Create a matrix with the arcs defined in a causlist object |
| nat_cte_times_vel_cpp | Multiply a Velocity by a constant real number |
| natParticle | R6 class that defines a Particle in the PSO algorithm |
| natPosition | R6 class that defines DBNs as vectors of natural numbers |
| nat_pos_minus_pos_cpp | Subtracts two natPositions to obtain the natVelocity that... |
| nat_pos_plus_vel_cpp | Add a velocity to a position |
| natPsoCtrl | R6 class that defines the PSO controller |
| natPsoho | Learn a DBN structure with a PSO approach |
| natVelocity | R6 class that defines velocities in the PSO |
| nat_vel_plus_vel_cpp | Adds two natVelocities |
| node_levels | Defines a level for every node in the net |
| nodes | Returns a list with the names of the nodes of a BN or a DBN |
| nodes.bn | Returns a list with the names of the nodes of a BN or a DBN |
| nodes.bn.fit | Returns a list with the names of the nodes of a BN or a DBN |
| nodes.dbn | Returns a list with the names of the nodes of a BN or a DBN |
| nodes.dbn.fit | Returns a list with the names of the nodes of a BN or a DBN |
| nodes_gen_exp | Generates the names of the nodes in t_0 and in all the... |
| nodes-set | Relabel the names of the nodes of a BN or a DBN |
| nodes-set-.bn | Relabel the names of the nodes of a BN or a DBN |
| nodes-set-.bn.fit | Relabel the names of the nodes of a BN or a DBN |
| nodes-set-.dbn | Relabel the names of the nodes of a BN or a DBN |
| nodes-set-.dbn.fit | Relabel the names of the nodes of a BN or a DBN |
| one_hot | One hot encoder for natural numbers without the 0. |
| one_hot_cpp | One-hot encoder for natural numbers without the 0 |
| ordering_gen_exp | Generates the names of n variables. |
| Particle | R6 class that defines a Particle in the PSO algorithm |
| 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 |
| Position | R6 class that defines DBNs as causality lists |
| pos_minus_pos_cpp | Subtracts two Positions to obtain the Velocity that... |
| pos_plus_vel_cpp | Add a velocity to a position |
| predict_bn | Performs inference over a fitted GBN |
| predict.dbn.fit | Performs inference in every row of a dataset with a DBN |
| 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 |
| PsoCtrl | R6 class that defines the PSO controller |
| psoho | Learn a DBN structure with a PSO approach |
| randomize_vl_cpp | Randomize a velocity with the given probabilities |
| rbn.dbn.fit | Simulates random samples from a fitted DBN |
| recount_arcs_exp | Experimental function that recounts the number of arcs in the... |
| reduce_freq | Reduce the frequency of the time series data in a data.table |
| rename_nodes_cpp | Return a list of nodes with the time slice appended up to the... |
| residuals.dbn.fit | Returns the residuals from fitting a DBN |
| score | Computes the score of a BN or a DBN |
| score.bn | Computes the score of a BN or a DBN |
| score.dbn | 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... |
| smooth_ts | Performs smoothing with the GDBN over a dataset |
| sub-subset-.dbn.fit | Replacement function for parameters inside DBNs |
| time_rename | Renames the columns in a data.table so that they end in... |
| trunc_geom | Geometric distribution sampler truncated to a maximum |
| Velocity | R6 class that defines velocities affecting causality lists in... |
| vel_plus_vel_cpp | Add two Velocities |
