View source: R/uncondMoments.R
get_regime_means_int | R Documentation |
\mu_{m}
get_regime_means
calculates regime means \mu_{m} = (I - \sum A)^(-1))
from the given parameter vector.
get_regime_means_int(
p,
M,
d,
params,
model = c("GMVAR", "StMVAR", "G-StMVAR"),
parametrization = c("intercept", "mean"),
constraints = NULL,
same_means = NULL,
weight_constraints = NULL,
structural_pars = NULL
)
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 "G-StMVAR" model considered? In the G-StMVAR model, the first |
parametrization |
|
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 B-matrix as well (it is |
Returns a (dxM)
matrix containing regime mean \mu_{m}
in the m:th column, m=1,..,M
.
No argument checks!
Kalliovirta L., Meitz M. and Saikkonen P. 2016. Gaussian mixture vector autoregression. Journal of Econometrics, 192, 485-498.
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 Unpublished working paper, available as arXiv:2109.13648.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
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.