Man pages for roqua/autovar
Automated Vector Autoregression Model Creation
| add_derived_column | Add a new column using data from other columns |
| add_trend | Adds a trend variable to a data set |
| contemporaneous_correlations_plot | Plot the contemporaneous correlations summary |
| convert_to_graph | Convert best model to graph |
| generate_network | Return a JSON array of network data of a fitting model... |
| generate_networks | Return a JSON array of network data of a fitting model |
| group_by | Split up a data set into different subsets |
| impute_dataframe | Impute missing values in a data.frame using EM imputation |
| impute_missing_values | Impute missing values |
| load_dataframe | Returns an av_state for data loaded from a data.frame |
| load_file | Load a data set from a .sav, .dta, or .csv file |
| order_by | Order the rows in a data set |
| plot_barchart | Plots a barchart of manual_score and the av_scores |
| print_accepted_models | Print a list of accepted models after a call to var_main |
| print_best_models | Prints the best model from the list of accepted models |
| print_rejected_models | Print a list of rejected models after a call to var_main |
| select_range | Select a subset of rows of a data set to be retained |
| select_relevant_columns | Select and return the relevant columns |
| select_relevant_rows | Select and return the relevant rows |
| set_timestamps | Add dummy variables for weekdays and day parts |
| store_file | Export a modified data set as an SPSS readable .sas file |
| vargranger_plot | Plot the Granger causality summary |
| var_info | Print summary information and tests for a VAR model... |
| var_main | Determine possibly optimal models for Vector Autoregression |
| var_summary | Print the output of var_main |
| visualize | Visualize columns of the data set |
| visualize_residuals | Visualize the residuals of a VAR model |
