Autovar is an R package for automating and simplifying the process from raw data to VAR models. For the actual VAR calculations, Bernhard Pfaff's vars package is used.
To install, type the following:
install.packages('devtools') require('devtools') install_github('roqua/autovar')
Documentation for this package can be found here.
library('autovar') # Example data sets can be found on https://autovar.nl av_state <- load_file("/path/to/file.dta") # Include models with (and without) trends in the search av_state <- add_trend(av_state) # Include models with (and without) day dummies in the search av_state <- set_timestamps(av_state, date_of_first_measurement = "2015-12-31", measurements_per_day = 1) # Search for VAR models for the variables Depression and Activity up to lag 3. av_state <- var_main(av_state, vars = c("Depression", "Activity"), lag_max = 3, log_level = 3) # Show the best models found print_best_models(av_state)