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MTS (version 1.2.1)

VAR: Vector Autoregressive Model

Description

Perform least squares estimation of a VAR model

Usage

VAR(x, p = 1, output = T, include.mean = T, fixed = NULL)

Arguments

x

A T-by-k matrix of k-dimensional time series

p

Order of VAR model. Default is 1.

output

A logical switch to control output. Default is with output.

include.mean

A logical switch. It is true if mean vector is estimated.

fixed

A logical matrix used in constrained estimation. It is used mainly in model simplification, e.g., removing insignificant estimates.

Value

data

Observed data

cnst

A logical switch to include the mean constant vector

order

VAR order

coef

Coefficient matrix

aic,bic,hq

Information criteria of the fitted model

residuals

Residuals

secoef

Standard errors of the coefficients to be used in model refinement

Sigma

Residual covariance matrix

Phi

AR coefficient polynomial

Ph0

The constant vector

Details

To remove insignificant estimates, one specifies a threshold for individual t-ratio. The fixed matrix is then defined automatically to identify those parameters for removal.

References

Tsay (2014, Chapter 3). Multivariate Time Series Analysis with R and Financial Applications. John Wiley. Hoboken, NJ.

See Also

refVAR command

Examples

Run this code
# NOT RUN {
data("mts-examples",package="MTS")
gdp=log(qgdp[,3:5])
zt=diffM(gdp)
m1=VAR(zt,p=2)
# }

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