Even something as simple as BEHR runs into trouble finding the right confidence interval for the fractional hardness ratio HR — it has a W-shaped posterior when the counts are low and the prior is aggressively non-informative, and tends to catch the edges of the range than the central bump.

]]>It seems to me that Xiao Li is telling us that MCMC methods are not a panacea for “fitting” (i.e. finding the modes and mapping out uncertainties) in multi-modal spaces. Considerable care must still be taken to make sure one covers the difficult parameter/probability space. ]]>