The main function of the BigVAR package. Performs cross validation to select penalty parameters over a training sample (as the minimizer of in-sample MSFE), then evaluates them over a test set. Compares against sample mean, random walk, AIC, and BIC benchmarks. Creates an object of class BigVAR.results
data(Y)
# Fit a Basic VARX-L with rolling cross validation Model1=constructModel(Y,p=4,struct='Basic',gran=c(50,10), verbose=FALSE)
results=cv.BigVAR(Model1)