[Pymc-user] Scaling of parameters
Status: Beta
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From: David H. <dav...@gm...> - 2006-04-27 13:32:38
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Hi, I'm using PyMC to sample from the distribution of two parameters, one whose domain is about [0,2] and the other [300,600]. Since they are correlated, I'm block updating the two together, ie. self.parameters('AB', init_val =3D [1, 500]) It appears that doing this is not efficient, in the sense that the jumps fo= r B are of the same order than for A. Hence, it takes a very long time to converge to the stationary distribution. Taking the log of B has allowed me to cut the number of simulations dramatically. Is this normal ? I thought that each parameter would get its own jump variance, with a correlation coefficient linking the two. Thanks, David |