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I run the same code by changing the initial slope parameter to m = 4. The first time I get an acceptance fraction: 0.2748 the second time 0.0.
I did a plot to see how the slope parameter varies with each iteration, during the second trial, it seems that the code is stuck at m = 4.
Does it has to do with how the metropolis-hastings method is being implemented?
The text was updated successfully, but these errors were encountered:
I expect so, yes! Can you free the sampler up by varying its proposal
distribution? Perhaps the prior on m is making life difficult?
On Thu, Apr 9, 2015 at 12:26 PM, Paula Sarkis [email protected]
wrote:
I run the same code by changing the initial slope parameter to m = 4. The
first time I get an acceptance fraction: 0.2748 the second time 0.0.
I did a plot to see how the slope parameter varies with each iteration,
during the second trial, it seems that the code is stuck at m = 4.
Does it has to do with how the metropolis-hastings method is being
implemented?
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Reply to this email directly or view it on GitHub #3.
I run the same code by changing the initial slope parameter to m = 4. The first time I get an acceptance fraction: 0.2748 the second time 0.0.
I did a plot to see how the slope parameter varies with each iteration, during the second trial, it seems that the code is stuck at m = 4.
Does it has to do with how the metropolis-hastings method is being implemented?
The text was updated successfully, but these errors were encountered: