VARXForecastEval {BigVAR} R Documentation

## Evaluate forecasts from a VAR or VARX with lag orders selected by AIC/BIC

### Description

Evaluate forecasts from a VAR or VARX with lag orders selected by AIC/BIC

### Usage

VARXForecastEval(Y, X, p, s, T1, T2, IC, h, iterated = FALSE)


### Arguments

 Y a T \times k multivariate time series X a T \times m multivariate time series of unmodeled exogenous variables p maximum lag order for endogenous series s maximum lag order for exogenous series T1 start of forecast evaluation period. T2 end of forecast evaluation period IC specifies whether to select lag order according to "AIC" or "BIC" h desired forecast horizon iterated indicator as to whether to use iterated or direct multistep forecasts (if applicable, VAR context only)

### Details

This function evaluates the one-step ahead forecasts of a VAR or VARX fit by least squares over an evaluation period. At every point in time, lag orders for the endogenous and exogenous series are selected according to AIC or BIC. This function is run automatically when cv.BigVAR is called unless ic is set to FALSE in constructModel.

### Value

Returns the one-step ahead MSFE as well as the forecasts over the evaluation period and lag order selected.

### References

Neumaier, Arnold, and Tapio Schneider. "Estimation of parameters and eigenmodes of multivariate autoregressive models." ACM Transactions on Mathematical Software (TOMS) 27.1 (2001): 27-57.

VARXFit,constructModel, cv.BigVAR

### Examples

data(Y)

# Evaluate the performance of a VAR with lags selected by BIC.
p <- 4
T1 <- floor(nrow(Y))/3
T2 <- floor(2*nrow(Y))/3
# Matrix of zeros for X
X <- matrix(0,nrow=nrow(Y),ncol=ncol(Y))
BICMSFE <- VARXForecastEval(Y,X,p,0,T1,T2,"BIC",1)



[Package BigVAR version 1.0.6 Index]