Closed slosar closed 12 years ago
This is harder than it sounds, at least in the general case. For example, if your mcmc-config floats a parameter that was previously fixed, how do we fill in the missing covariances that the MCMC algorithm expects? I think you were specifically interested in changing/removing priors, right? Why does the fit need different priors than MCMC?
I need for the following reasons:
You want boxpriors on anistropic params, but fitting with box priors often results in minuit failing. So the rigth thing to do is to fit with a strongish gaussian priors and then do an unbiased MCMC with boxpriors. In principle I think I should be able to just run MCMC with default errors as a diagonal proposal matrix...
anže
On Sun, 9 Sep 2012, dkirkby wrote:
This is harder than it sounds, at least in the general case. For example, if your mcmc-config floats a parameter that was previously fixed, how do we fill in the missing covariances that the MCMC algorithm expects? I think you were specifically interested in changing/removing priors, right? Why does the fit need different priors than MCMC?
Reply to this email directly or view it on GitHub: https://github.com/deepzot/baofit/pull/4#issuecomment-8407559
It sounds like the underlying problem is that minuit doesn't like box priors. I suspect this is because I made the edges too sharp and it doesn't like the discontinuity. I am going to add an option for softer edges and see if this helps.
I am closing this, assuming that the new soft box priors will eliminate most cases of box priors not working with MINUIT. Also, the new mcmc-reset option allows you to ignore the MINUIT covariance for MCMC (but does not let you change the priors).
This time done in a much simpler way that modified only one file and really really should work, but it doesn't.... David, do you understand why?