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 |

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