MSBVAR (version 0.9-2)

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)

Arguments

m1

Matrix of VAR forecasts produced by forecast.VAR.

m2

Matrix of VAR forecasts or a matrix of real data to compare to forecasts.

Value

An object with two elements:

rmse

Forecast RMSE

mae

Forecast MAE

Details

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

See Also

forecast 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(fit.bvar, nsteps=nrow(Y.sample2))

# Compare forecasts to real data
cf.forecasts(forecasts[(nrow(Y.sample1)+1):nrow(forecasts),], Y.sample2)