[ADMB Users] mceval output inconsistent with mcmc display

Thu Jun 9 21:42:47 PDT 2011

On 11-06-09 09:23 PM, Campbell, Alex wrote:

Still not enough information to understand completely.
However do you have real priors on all the parameters.
I recall fitting a model where the posterior was improper.

That means the integral over all the parameters was infinity.
This manifested itself in the parameters from the mcmc looking OK for a 
while and
then just wandering off to what would like like junk values. the problem 
is that if you
have a set of "reasonable" values with proabability eps and a huge set 
of stupid values
with probability 1-eps  if you run the mcmc long enough it will spend 
most of its time
lost in the stupid values.

> No, I'm concerned that the displayed likelihood is not consistent with
> the likelihood corresponding to the parameters obtained via mceval at
> that point (at that iteration).
>
> Here's some output. Beginning of mcmc:
>
> Initial seed value -36519
> 785.580219414446 785.580219414446
>   mcmc sim 1  acceptance rate 0 0
> 785.580219414446 785.580219414446
>   mcmc sim 201  acceptance rate 0 0
> decreasing step size -2049.27939913456
> 750.625386694123 750.625386694123
>   mcmc sim 401  acceptance rate 0.0773067331670823 0.155
> 739.336552314425 739.336552314425
>   mcmc sim 601  acceptance rate 0.114808652246256 0.19
>
> Last few hundred iterations:
>
> 602.449537531548 602.449537531548
>   mcmc sim 999401  acceptance rate 0.036780031238712 0.03
> 602.366020956481 602.366020956481
>   mcmc sim 999601  acceptance rate 0.0367746730945647 0.01
> 603.32884634525 603.32884634525
>   mcmc sim 999801  acceptance rate 0.0367683168950621 0.005
>
> And not much variation in between - lowest likelihood around 590.
>
> But the likelihood for parameters read from psv by mceval is terrible,
> around -600, at least after the first few hundred iterations.
>
> The trace of primary parameters shows them moving from a sensible region
> very quickly to a rubbish region.
>
>
> -----Original Message-----
> From: dave fournier [mailto:davef at otter-rsch.com]
> Sent: Friday, 10 June 2011 1:08 PM
> To: Campbell, Alex
> Subject: Re: [ADMB Users] mceval output inconsistent with mcmc display
>
> On 11-06-09 07:34 PM, Campbell, Alex wrote:
>
>
> So if I understand this you think the value should be closer to the
> mode.
> Intuition about this is wrong.  In high dimensions you never get
> anywhere near the mode.
> Think of a standard n dimensional multivariate normal. You can easily
> see that the pdf for the distance r from 0 is prop. to
> r^{n-1}*exp(-r^2/2}.
> Do a quick calc to see what the probability is that you will get to
> within distance 1 of 0 when the dimension is 100. You may be surprised.
>
>
>
>> Sorry yes it is the log likelihood. I was unclear.
>>
>> Mode estimate: approx 750 log likelihood. MCMC display output: ranges
>> from 600 to 750 over one million iterations. Parameters read from psv
>> file using mceval: around -600 after the first few hundred iterations.
>>
>> Thanks Ian that's exactly the sort of investigative tool I think I
> need.
>> -alex
>>
>> -----Original Message-----
>> From: users-bounces at admb-project.org
>> [mailto:users-bounces at admb-project.org] On Behalf Of dave fournier
>> Sent: Friday, 10 June 2011 8:41 AM
>> To: users at admb-project.org
>> Subject: Re: [ADMB Users] mceval output inconsistent with mcmc display
>>
>> Probably better to make a little example first.
>> for example
>> DATA_SECTION
>> PARAMETER_SECTION
>>      init_vector x(1,10)
>>      sdreport_vector rx(1,10);
>>      objective_function_value f
>> PROCEDURE_SECTION
>>      f=0.5*norm2(x);
>>      rx=x;
>>      if (mceval_phase())
>>      {
>>        cout<<   f<<   ""<<   x<<   endl;
>>      }
>>
>> then running it with
>>
>>     ./small -mcmc 100000 -mcsave 1
>>
>> and the screen shows
>>
>> mcmc sim 1  acceptance rate 0 0
>> -4.04084 -4.04084
>>     mcmc sim 201  acceptance rate 0.169154 0.17
>> -2.76404 -2.76404
>>     mcmc sim 401  acceptance rate 0.187032 0.205
>> -5.52107 -5.52107
>>     mcmc sim 601  acceptance rate 0.189684 0.195
>> -6.00142 -6.00142
>>     mcmc sim 801  acceptance rate 0.187266 0.18
>> -4.85913 -4.85913
>>     mcmc sim 1001  acceptance rate 0.182817 0.165
>> -1.51622 -1.51622
>>     mcmc sim 1201  acceptance rate 0.181515 0.175
>> -3.43209 -3.43209
>>
>> So this is the log-likelihood *NOT* minus the log-likelihood. Also it
>> is every 200'th value. (Just printed out for amusement).
>>
>>
>>
>>
>>
>>
>>
>>
>>
>>
>>
>> ~
>>
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>
>
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