VAR: Vector Autoregressive Model

Description Usage Arguments Details Value Author(s) References See Also Examples

Description

Perform least squares estimation of a VAR model

Usage

1
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 simplifcation, e.g., removing insignificant estimates.

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.

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

Author(s)

Ruey S. Tsay

References

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

See Also

refVAR command

Examples

1
2
3
4
data("mts-examples",package="MTS")
gdp=log(qgdp[,3:5])
zt=diffM(gdp)
m1=VAR(zt,p=2)

Example output

Constant term: 
Estimates:  0.001258163 0.001231581 0.002895581 
Std.Error:  0.0007266338 0.0007382941 0.000816888 
AR coefficient matrix 
AR( 1 )-matrix 
      [,1]  [,2]   [,3]
[1,] 0.393 0.103 0.0521
[2,] 0.351 0.338 0.4691
[3,] 0.491 0.240 0.2356
standard error 
       [,1]   [,2]   [,3]
[1,] 0.0934 0.0984 0.0911
[2,] 0.0949 0.1000 0.0926
[3,] 0.1050 0.1106 0.1024
AR( 2 )-matrix 
        [,1]   [,2]     [,3]
[1,]  0.0566  0.106  0.01889
[2,] -0.1914 -0.175 -0.00868
[3,] -0.3120 -0.131  0.08531
standard error 
       [,1]   [,2]   [,3]
[1,] 0.0924 0.0876 0.0938
[2,] 0.0939 0.0890 0.0953
[3,] 0.1038 0.0984 0.1055
  
Residuals cov-mtx: 
             [,1]         [,2]         [,3]
[1,] 2.824442e-05 2.654091e-06 7.435286e-06
[2,] 2.654091e-06 2.915817e-05 1.394879e-05
[3,] 7.435286e-06 1.394879e-05 3.569657e-05
  
det(SSE) =  2.258974e-14 
AIC =  -31.13328 
BIC =  -30.726 
HQ  =  -30.96783 

MTS documentation built on May 29, 2017, 5:15 p.m.

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