Man pages for LBNL-ETA/RMV2.0
M&V2.0 Using R and Shiny
| acf_plot | Residual autocorrelation plot |
| act_plot | Plot of the actual pre or post installation data |
| act_vs_fit_plot | actual vs. fitted scatter plot |
| axis_range | Compute plot axis range for two different data files (e.g,... |
| clean_eload | Clean the elaod data |
| clean_Temp | Clean the Temperature data |
| clean_Temp_2 | Clean the Temperature data |
| convert_15min_to_1_hour | Convert 15 minute interval data into hourly interval data |
| cpt_det | Function to detect potential non-routine events |
| cpt_save_plot | Plot the residual/savings and the identified change points in... |
| create_date_var | Create an input variable corresponding to given intervals |
| cusum_plot | Plot the CUSUM |
| daily_cusum_barplot | Plot the daily CUSUM |
| daily_save_barplot | BarPlot the daily savings |
| data_load | Load data into the shiny application |
| days_off_var | Create a new binary variable based on the dates of days off... |
| detect_interval | Compute the granularity of the time series |
| eload_heatmap | Eload heatmap |
| eload_vs_input_plot | eload vs. Temperature scatter plot |
| errors_vs_input_plot | errors vs. Temperature scatter plot |
| gbm_baseline | Gradient boosting machine baseline model function. |
| gbm_tune | Gradient boosting machine tuning function. |
| k_dblocks_cv | K-fold-day cross validation function. |
| k_wblocks_cv | K-fold-week cross validation function. |
| load_session | load a session |
| monthly_cusum_barplot | BarPlot the monthly CUSUM |
| monthly_save_barplot | BarPlot the monthly savings |
| nre_eval | Function to identify change points in the whole dataset |
| number_of_days | Compute number of days in the data |
| portfolio_savings | Portfolio Savings summary |
| post_plot | Plot of the post-installation period data |
| pred_accuracy | Prediction accuracy metrics computation |
| pre_plot | Plot of the pre-installation period data |
| ratio_missing | Estimate the ration of missing data |
| save_plot | Plot the residual in the prediction period |
| save_predictions | Predictions Data Savings |
| save_session | Save a session |
| savings | Function to calculate the savings of the post period. |
| savings_heatmap | Savings heatmap |
| savings_results_plot | Savings barplot |
| savings_summary | Savings summary |
| screen_pie_plot | Screening pie plot |
| screen_summary | Screening summary |
| time_features | Extract features from the time |
| time_format | Convert the timestamps into the default format |
| to_exclude | Exclude data from given intervals |
| to_extract | Extract data from given intervals |
| towt_baseline | Time Of the Week and Temperature baseline model function. |
| towt_time_var | Convert the time format |
| train_model | Train Baseline models |
| train_model_summary | Baseline models results summary |
| weekly_cusum_barplot | BarPlot the weekly CUSUM |
| weekly_save_barplot | BarPlot the weekly savings |
