MSBVAR (version 0.2.2)

cf.forecasts: Compare VAR forecasts to each other or real data

Description

Computes the root mean sqaured error and mean absolute error for a series of forecasts or for forecasts and real data.

Usage

cf.forecasts(m1, m2)

Value

An object with two elements:rmseForecast RMSEmaeForecast MAE

Details

Simple RMSE and MAE computation for the forecasts. The reported values are summed over the series and time points.

See Also

forecast.VAR for forecast computations

Examples

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)