Am 23.05.2024 um 18:15 schrieb Alecos Papadopoulos:
I realized that I am a bit confused as to what happens with the
various VCV matrices when Kalman Filter is used together with maximum
likelihood. Assume a time-invariant state space model.
What I understand is the following:
The Kalman Filter will run as usual and will provide the various VCV
estimates as described in Ch. 36 of the user's guide, based, in the
end, on the final ML estimates to obtain the residual series (the etas
and the epsilons).
But at the same time, we may have asked the mle to estimate also the
elements of the VCV matrices, (see eg. the ARMA estimation example
Listing 36.1). This will give us another, different estimate of the
VCV matrices... or will this agree with the KF estimates above, due
perhaps to the fact that this is Normal mle that we necessarily assume?
Hi, I'm looking at listing 36.1 but I'm not exactly sure what you mean,
sorry. Are you talking about sigma there?
Apart from that, jack can probably comment some more, but I think he is
currently unavailable.
cheers
sven
_______________________________________________
Gretl-users mailing list -- gretl-users@gretlml.univpm.it
To unsubscribe send an email to gretl-users-le...@gretlml.univpm.it
Website:
https://gretlml.univpm.it/postorius/lists/gretl-users.gretlml.univpm.it/
