View source: R/loglikelihood.R
get_alpha_mt | R Documentation |
get_alpha_mt
computes the mixing weights based on
the logarithm of the multivariate normal densities in the definition of
the mixing weights.
get_alpha_mt(M, log_mvdvalues, alphas, epsilon, conditional, also_l_0 = FALSE)
M |
|
log_mvdvalues |
|
alphas |
|
epsilon |
the smallest number such that its exponent is wont classified as numerically zero
(around |
conditional |
a logical argument specifying whether the conditional or exact log-likelihood function should be used. |
also_l_0 |
return also l_0 (the first term in the exact log-likelihood function)? |
Note that we index the time series as -p+1,...,0,1,...,T
as in Kalliovirta et al. (2016).
Returns the mixing weights a matrix of the same dimension as log_mvdvalues
so
that the t:th row is for the time point t and m:th column is for the regime m.
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 Unpublished working paper, available as arXiv:2109.13648.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
loglikelihood_int
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