VMA Model with Selected Lags

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Description

Performs the conditional maximum likelihood estimation of a VMA model with selected lags in the model

Usage

1
VMAs(da, malags, include.mean = T, fixed = NULL, prelim = F, details = F, thres = 2)

Arguments

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

Details

A modified version of VMA model by allowing the user to select non-zero MA lags

Value

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

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

VMA

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