Closed steveschulze closed 6 years ago
Hi Steve, the probability is the posterior probability, defined as in Bayes theorem
P(Theta|M,D) = P(D|M,Theta) * P(Theta|M) / P(D)
While the likelihood is just the term P(Theta|M).
In the case of a Gaussian likelihood (the one assumed by default in Beagle), the likelihood is proportional to the square of the residuals, i.e. to a chi-square goodness-of-fit measure.
It makes sense, however, to also include a chi-square in the Beagle output, as it is a useful quantity when interpreting the results.
Thanks a lot! It would be fantastic to add the chi-square to Beagle output.
as @eclake made me noticing, the probability is not exactly what I stated above, it is the weight (they sum up to 1) required to sample from the Multinest output to be able to produce MCMC-like samples (equation 9 of Feroz+2009)
available in version >= 0.19.6
Thanks a lot for adding this feature.
Hi Jacopo,
The extension "POSTERIOR PDF" in the BEAGLE output has a column "probability" and "ln likelihood". What is the difference between them? Does BEAGLE provide a figure for the goodness of fit?
Cheers,
Steve