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

In MSBVAR: Markov-Switching, Bayesian, Vector Autoregression Models

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.

Details

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

Value

An object with two elements:

rmse	Forecast RMSE
mae	Forecast MAE

Author(s)

Patrick T. Brandt

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)

Example output

##
## MSBVAR Package v.0.9-2
## Build date:  Thu Jul 20 09:22:07 2017 
## Copyright (C) 2005-2017, Patrick T. Brandt
## Written by Patrick T. Brandt
##
## Support provided by the U.S. National Science Foundation
## (Grants SES-0351179, SES-0351205, SES-0540816, and SES-0921051)
##

[1] 85.50756 57.04836

MSBVAR documentation built on May 30, 2017, 1:23 a.m.