Bayesian estimation _ mode_computation

[KKLS]

thanks for the quick reply Prof. Pfeifer:

A bit confused though. I am citing below one of your comments which can be found under the following link:

Model Comparison Bayesian Estimation (again)

Hello, I read the relevant forum topics on this already, still not 100% sure I am doing it right, so some short questions are remaining: I am basically comparing one model in 2 different versions, the second version differs only in one equation of the model block. I am using the same data for both models. I am using the same priors for the two models (althought the second model does contain additional parameters that didnt have to be estimated in the first - (1) does that bias the posterior od…

Re: Model Comparison Bayesian Estimation (again)
Postby Peter Zar » Thu Sep 03, 2015 9:00 am

Hi together,
just one more question in the same context: If I estimate a model M1 and get
Log data density [Laplace approximation] is -480, then I estimate a different version M2 (change priors but same data) and get
Log data density [Laplace approximation] is -490
then M1 is preferred by the data by a Bayes factor of exp(10), correct?

Best, Peter
Peter Zar Posts: 10Joined: Tue Jan 21, 2014 12:02 pm

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Re: Model Comparison Bayesian Estimation (again)
Postby jpfeifer » Thu Sep 03, 2015 6:58 pm

Exactly.

In the cited text above one asks you regarding model comparison using

Log data density [Laplace approximation]

and you approve. Is that right?
I am confused : How can I calculate the statistics you mention: IIs it already provided by dynare (I do not seem to find such a statistic)

Final value of minus the log posterior (or likelihood):-569.338740

in my mode computation.