VARXFit {BigVAR}R Documentation

Fit a VAR or VARX model by least squares

Description

Fit a VAR or VARX model by least squares

Usage

VARXFit(Y, p, IC, VARX = NULL)

Arguments

Y

a t \times k multivariate time series

p

maximum lag order

IC

Information criterion indicator, if set to NULL, it will fit a least squares VAR(X) of orders p and s. Otherwise, if set to "AIC" or "BIC" it return the model with lag orders that minimize the given IC.

VARX

a list of VARX specifications (as in constructModel (or NULL )

Details

This function uses a modified form of the least squares technique proposed by Neumaier and Schneider (2001). It fits a least squares VAR or VARX via a QR decomposition that does not require explicit matrix inversion. This results in improved computational performance as well as numerical stability over the conventional least squares approach.

Value

Returns a list with four entries:

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.

See Also

constructModel, cv.BigVAR,BigVAR.fit

Examples

data(Y)
# fit a VAR_3(3)
mod <- VARXFit(Y,3,NULL,NULL)
# fit a VAR_3 with p= 6 and lag selected according to AIC
modAIC <- VARXFit(Y,6,"AIC",NULL)
# Fit a VARX_{2,1} with p=6, s=4 and lags selected by BIC
modXBIC <- VARXFit(Y,6,"BIC",list(k=1,s=4))


[Package BigVAR version 1.0.6 Index]