Thanks - your explanations helped me a lot!
Best wishes,
Matthias
Klaas Enno Stephan schrieb:
> Dear Matthias,
>
> There is no need for any further comparisons since you have already
> done the right thing, i.e. applying BMS to the entire space of models
> considered. You can now simply report which model was optimal, state
> its expected posterior probability (or its exceedance probability) in
> relation to the other models, and report its parameter estimates.
>
> Generally, note that selective comparisons of subsets of models are
> not equivalent to a proper model space partitioning approach unless
> you are using the agglomerative property of the Dirichlet
> distribution. As explained in the discussion of our BMS paper, the
> posterior belief about which model is most likely to have generated
> the data is a function of the entire set of models considered. This
> means that changing model space (by reducing or extending the number
> of models considered) can change one's inference about the optimal
> model. As a consequence, one should always infer the most likely
> model by comparing the entire set of plausible models at once.
>
> Best wishes,
> Klaas
>
>
>
> ------------------------------------------------------------------------
> *Von:* Matthias Schurz <[log in to unmask]>
> *An:* [log in to unmask]
> *Gesendet:* Dienstag, den 14. Juli 2009, 15:48:22 Uhr
> *Betreff:* Re: [SPM] DCM BMS results interpretation
>
> Dear Dr. Stephan,
>
> I'm glad to hear that the model space partitioning approach will be
> further
> developed. At the moment, i would like to write up the study of which
> i was
> showing the results - with 16 models better than 48. Until the new
> method is
> available: do you think a simple comparison of a single model out of the
> best 16 (the worst among them) against a single model out of the worst 48
> (the best among them) would also show that those 16 models are superior to
> the 48?
> Please see the .pdf file for clarification.
>
> Matthias
>
|