cf.forecasts {MSBVAR} | R Documentation |
Computes the root mean sqaured error and mean absolute error for a series of forecasts or for forecasts and real data.
cf.forecasts(m1, m2)
m1 |
Matrix of VAR forecasts produced by forecast.VAR . |
m2 |
Matrix of VAR forecasts or a matrix of real data to compare to forecasts. |
Simple RMSE and MAE computation for the forecasts. The reported values are summed over the series and time points.
An object with two elements:
rmse |
Forecast RMSE |
mae |
Forecast MAE |
Patrick T. Brandt
forecast.VAR
for forecast computations
data(IsraelPalestineConflict) Y.sample1 <- window(IsraelPalestineConflict, end=c(2002, 52)) Y.sample2 <- window(IsraelPalestineConflict, start=c(2003,1)) # Fit a BVAR model fit.bvar <- szbvar(Y.sample1, p=6, lambda0=0.6, lambda1=0.1, lambda3=2, lambda4=0.25, lambda5=0, mu5=0, mu6=0, prior=0) # Forecast -- this gives back the sample PLUS the forecasts! forecasts <- forecast.VAR(fit.bvar, nsteps=nrow(Y.sample2)) # Compare forecasts to real data cf.forecasts(forecasts[(nrow(Y.sample1)+1):nrow(forecasts),], Y.sample2)