Man pages for LBNL-ETA/RMV2.0
M&V2.0 Using R and Shiny

acf_plotResidual autocorrelation plot
act_plotPlot of the actual pre or post installation data
act_vs_fit_plotactual vs. fitted scatter plot
axis_rangeCompute plot axis range for two different data files (e.g,...
clean_eloadClean the elaod data
clean_TempClean the Temperature data
clean_Temp_2Clean the Temperature data
convert_15min_to_1_hourConvert 15 minute interval data into hourly interval data
cpt_detFunction to detect potential non-routine events
cpt_save_plotPlot the residual/savings and the identified change points in...
create_date_varCreate an input variable corresponding to given intervals
cusum_plotPlot the CUSUM
daily_cusum_barplotPlot the daily CUSUM
daily_save_barplotBarPlot the daily savings
data_loadLoad data into the shiny application
days_off_varCreate a new binary variable based on the dates of days off...
detect_intervalCompute the granularity of the time series
eload_heatmapEload heatmap
eload_vs_input_ploteload vs. Temperature scatter plot
errors_vs_input_ploterrors vs. Temperature scatter plot
gbm_baselineGradient boosting machine baseline model function.
gbm_tuneGradient boosting machine tuning function.
k_dblocks_cvK-fold-day cross validation function.
k_wblocks_cvK-fold-week cross validation function.
load_sessionload a session
monthly_cusum_barplotBarPlot the monthly CUSUM
monthly_save_barplotBarPlot the monthly savings
nre_evalFunction to identify change points in the whole dataset
number_of_daysCompute number of days in the data
portfolio_savingsPortfolio Savings summary
post_plotPlot of the post-installation period data
pred_accuracyPrediction accuracy metrics computation
pre_plotPlot of the pre-installation period data
ratio_missingEstimate the ration of missing data
save_plotPlot the residual in the prediction period
save_predictionsPredictions Data Savings
save_sessionSave a session
savingsFunction to calculate the savings of the post period.
savings_heatmapSavings heatmap
savings_results_plotSavings barplot
savings_summarySavings summary
screen_pie_plotScreening pie plot
screen_summaryScreening summary
time_featuresExtract features from the time
time_formatConvert the timestamps into the default format
to_excludeExclude data from given intervals
to_extractExtract data from given intervals
towt_baselineTime Of the Week and Temperature baseline model function.
towt_time_varConvert the time format
train_modelTrain Baseline models
train_model_summaryBaseline models results summary
weekly_cusum_barplotBarPlot the weekly CUSUM
weekly_save_barplotBarPlot the weekly savings
LBNL-ETA/RMV2.0 documentation built on May 16, 2018, 11:12 a.m.