[ADMB Users] mceval output inconsistent with mcmc display

[Campbell, Alex]

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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