Displaying 1 result from an estimated 1 matches for "log_residuals".
2010 Feb 07
1
Out-of-sample prediction with VAR
...se that I am doing it right, how is it possible that a
automatically fitted model with more variables actually performs less good
(in terms of MAPE)? Shouldn't it at least predict just as well as the
simple AR(3) by finding that the extra variables have no added value?
My code:
ts_Y <- ts(log_residuals[1:104]); # detrended sales data
ts_XGG <- ts(salesmodeldata$gtrends_global[1:104]);
ts_XGL <- ts(salesmodeldata$gtrends_local[1:104]);
training_matrix <- data.frame(ts_Y, ts_XGG, ts_XGL);
### Try VAR(3)
var_model <- VAR (y=training_matrix, p=3, type="both", season=NULL,...