VMA Model with Selected Lags
Performs the conditional maximum likelihood estimation of a VMA model with selected lags in the model
VMAs(da, malags, include.mean = T, fixed = NULL, prelim = F, details = F, thres = 2)
da |
A T-by-k matrix of a k-dimensional time series with T observations |
malags |
A vector consisting of non-zero MA lags |
include.mean |
A logical switch to include the mean vector |
fixed |
A logical matrix to fix coefficients to zero |
prelim |
A logical switch concerning initial estimation |
details |
A logical switch to control output level |
thres |
A threshold value for setting coefficient estimates to zero |
A modified version of VMA model by allowing the user to select non-zero MA lags
data |
The observed time series |
MAlags |
The VMA lags |
cnst |
A logical switch to include the mean vector |
coef |
The parameter estimates |
secoef |
The standard errors of the estimates |
residuals |
Residual series |
aic,bic |
The information criteria of the fitted model |
Sigma |
Residual covariance matrix |
Theta |
The VMA matrix polynomial |
mu |
The mean vector |
MAorder |
The VMA order |
Ruey S. Tsay
Tsay (2014, Chapter 3). Multivariate Time Series Analysis with R and Financial Applications. John Wiley. Hoboken, NJ.
VMA
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