[Pymc-user] Correlation between parameters

[David H. <dav...@et...>]

I have a model with two parameters A and B. When I compute their
distribution using PyMC, I get a 'cigar' distribution, in other words,
parameters A and B are strongly correlated. I figure this must put a
strain on the routine, forcing it to decrease the jump radius to
maintain an acceptable acceptance ratio.  Is there a way to indicate
that those parameters are correlated and to use a multivariate
distribution for the jumps ?


Thanks, 


David


P.S. Adding the generalized extreme distribution to flib would sure be
appreciated.