train_model: Train Baseline models

In LBNL-ETA/RMV2.0: M&V2.0 Using R and Shiny

Description

train_model This function is used by the shiny application to train the baseline models for all the data that are stored in the var_out object

Usage

train_model(var_out, screen = T, Model = "TOWT", pam_list = NULL,
  days_off_path = NULL)

Arguments

var_out	a shiny reactiveValues object where the taining data are stored
screen	Boolean that determines if the analysis is a screening or a savings analysis. If it's a screening then the baseline model will return only the fitting results of the pre-installation period. While if it's savings analysis the baseline model will also return the predictions for the post-installation period
Model	Character string that correspond to the name of the used model
pam_list	A list with information about the hyperparameters of the considered model
days_off_path	A path of the file that include the date of the days off (i.e., holidays)

Value

train_model a list that contains a list of the results and a vector of indices data where the model failed to produce a result

LBNL-ETA/RMV2.0 documentation built on Nov. 9, 2020, 5:44 a.m.