View source: R/parameterReforms.R
reform_constrained_pars  R Documentation 
reform_constrained_pars
reforms constrained parameter vector
into the form that corresponds to unconstrained parameter vectors.
reform_constrained_pars(
p,
M,
d,
params,
model = c("GMVAR", "StMVAR", "GStMVAR"),
constraints = NULL,
same_means = NULL,
weight_constraints = NULL,
structural_pars = NULL,
change_na = FALSE
)
p 
a positive integer specifying the autoregressive order of the model. 
M 

d 
the number of time series in the system. 
params 
a real valued vector specifying the parameter values.
Above, In the GMVAR model, The notation is similar to the cited literature. 
model 
is "GMVAR", "StMVAR", or "GStMVAR" model considered? In the GStMVAR model, the first 
constraints 
a size 
same_means 
Restrict the mean parameters of some regimes to be the same? Provide a list of numeric vectors
such that each numeric vector contains the regimes that should share the common mean parameters. For instance, if

weight_constraints 
a numeric vector of length 
structural_pars 
If
See Virolainen (forthcoming) for the conditions required to identify the shocks and for the Bmatrix as well (it is 
change_na 
change NA parameter values of constrained models to 9.999? 
Returns "regular model" parameter vector corresponding to the constraints.
No argument checks!
Kalliovirta L., Meitz M. and Saikkonen P. 2016. Gaussian mixture vector autoregression. Journal of Econometrics, 192, 485498.
Virolainen S. (forthcoming). A statistically identified structural vector autoregression with endogenously switching volatility regime. Journal of Business & Economic Statistics.
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 Unpublished working paper, available as arXiv:2109.13648.
@keywords internal
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