fitGSMVARDEPRECATED! USE THE FUNCTION alt_gsmvar INSTEAD! alt_gsmvar constructs
a GMVAR model based on results from an arbitrary estimation round of fitGSMVAR.
alt_gmvar(
gmvar,
which_round = 1,
which_largest,
calc_cond_moments = TRUE,
calc_std_errors = TRUE
)Returns an object of class 'gsmvar' defining the specified reduced form or structural GMVAR,
StMVAR, or G-StMVAR model. Can be used to work with other functions provided in gmvarkit.
Note that the first autocovariance/correlation matrix in $uncond_moments is for the lag zero,
the second one for the lag one, etc.
object of class 'gmvar'
based on which estimation round should the model be constructed? An integer value in 1,...,ncalls.
based on estimation round with which largest log-likelihood should the model be constructed?
An integer value in 1,...,ncalls. For example, which_largest=2 would take the second largest log-likelihood
and construct the model based on the corresponding estimates. If used, then which_round is ignored.
should conditional means and covariance matrices should be calculated?
Default is TRUE if the model contains data and FALSE otherwise.
should approximate standard errors be calculated?
It's sometimes useful to examine other estimates than the one with the highest log-likelihood. This function
is wrapper around GSMVAR that picks the correct estimates from an object returned by fitGSMVAR.
Kalliovirta L., Meitz M. and Saikkonen P. 2016. Gaussian mixture vector autoregression. Journal of Econometrics, 192, 485-498.
Kalliovirta L. and Saikkonen P. 2010. Reliable Residuals for Multivariate Nonlinear Time Series Models. Unpublished Revision of HECER Discussion Paper No. 247.
Virolainen S. 2022. Gaussian and Student's t mixture vector autoregressive model with application to the asymmetric effects of monetary policy shocks in the Euro area. Unpublished working paper, available as arXiv:2109.13648.
Virolainen S. 2025. A statistically identified structural vector autoregression with endogenously switching volatility regime. Journal of Business & Economic Statistics, 43, 1, 44-54.
alt_gsmvar