[ADMB Users] Fail to get convergence
Saang-Yoon
shyunuw at gmail.com
Tue Nov 11 09:07:03 PST 2014
Dr. Fournier. Yes, it runs!!! GREAT!!! Thank you very much for your
help.
Saang-Yoon
On Tuesday, November 11, 2014 10:36:09 AM UTC-5, dave fournier wrote:
> On 11/10/2014 09:23 PM, Saang-Yoon wrote:
>
> Hi, Dr. Fournier and Hans.
> Attached are two TPL files:
> (1) ssmbr3v3.TPL, which is based on Hans' link below (i.e., the page in
> the ADMB manual).
> (2) ssmbr3v4.TPL, which is based on Dr. Fournier's suggestion below.
> Although both files still fail to generate its corresponding COR file,
> the 1st TPL (i.e., ssmbr3v3.TPL) is better than the 2nd TPL (i.e.,
> ssmbr3v4.TPL). Would you mind checking those attached TPL files? FYI,
> following are the command for run:
>
> admb -r -s ssmbr3v3.tpl
> ssmbr3v3 -ind simdataall2.dat -ainp ssmbr3v3.pin -phase 3 -noinit
>
> admb -r -s ssmbr3v4.tpl
> ssmbr3v4 -ind simdataall2.dat -ainp ssmbr3v4.pin -phase 3 -noinit
>
> Again thank you very much.
> Saang-Yoon
>
>
> The code for the choleski factor should look more like this.
> I changed both and the model runs fine.
>
>
> dvar_matrix L(1,nages,1,nages); // Cholesky factor
> L.initialize();
> L(1,1)=1;
> L(2,1)=rp/sqrt(1+rp*rp);
> L(2,2)=1/sqrt(1+rp*rp);
> L(3,2)=sp/sqrt(1+sp*sp);
> L(3,3)=1/sqrt(1+sp*sp);
>
> However the bounds on rp and ro are probably not what you want.
>
>
>
>
>
>
> On Thursday, November 6, 2014 10:30:11 AM UTC-5, Hans wrote:
>
>> See also:
>>
>>
>> http://www.admb-project.org/examples/admb-tricks/parameterization/covariance-matrices/covariance-matrices
>>
>> Hans
>>
>> On Thu, Nov 6, 2014 at 4:23 PM, dave fournier <da... at otter-rsch.com>
>> wrote:
>>
>>> On 11/05/2014 05:10 PM, Saang-Yoon wrote:
>>>
>>> As I said, you should work with the Choleski decomposition of the
>>> correlation matrix.
>>>
>>> In the simple 3x3 case your conditions imply that it is determined by 2
>>> parameters
>>>
>>> r and s with bounds a and b such that a<=r<=b. You get a and b by
>>> solving
>>>
>>> 0.0<= r/sqrt(1+r*r) <=0.7
>>>
>>> The matrix is
>>>
>>> 1 0 0
>>>
>>> r/sqrt(1+r*r) 1/sqrt(1+r*r) 0
>>>
>>> 0 s/sqrt(1+s*s) 1/sqrt(1+s*s)
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>> Hi, Dr. Fournier and others.
>>> I made some progress. Exploring many possibilities, I found that the
>>> following assumptions help, but there is still a concern.
>>> (Assumption 1) Three age classes are not from the same cohort, and thus
>>> age class 1 and 3 are presumed to be independent. Thus I fix the
>>> correlation coefficient between age class 1 and 3 as zero.
>>> (Assumption 2) If there is a correlation between neighbor age classes
>>> (e.g., "1 vs. 2", and "2 vs. 3"), the correlation should be positive (i.e.
>>> autocorrelation over the years). Thus I set bounds of correlation
>>> between those neighbor classes to be positive: (e.g., init_bounded_number
>>> corp12(0.0,0.7,3); )
>>>
>>> Then now I have the resultant COR file (i.e., convergence was made).
>>> It was good news, but the estimates of correlation coefficients between
>>> neighbor age classes are stuck to the uppder bound, 0.7. If I allow a wide
>>> bound (e.g., init_bounded_number corp12(0.0,0.9,3); ), then I failed to get
>>> positive definite matrices.
>>>
>>> admb -r -s ssmbr3v4.tpl
>>> ssmbr3v4 -ind simdataall2.dat -ainp ssmbr3v3.pin -phase 1 -noinit
>>>
>>> Any advice would be appreciated. Best Wishes,
>>> Saang-Yoon
>>>
>>> On Tuesday, November 4, 2014 6:30:56 PM UTC-5, dave fournier wrote:
>>>
>>>> On 11/04/2014 02:58 PM, Saang-Yoon wrote:
>>>>
>>>> Hmm. Well its like this. Pick a number between -infinity and +
>>>> infinity. Why would you expect that it would need to be positive.
>>>>
>>>> or a matrix like
>>>>
>>>> 1 .9 .9
>>>> .9 1 -.50
>>>> .9 -.50 1
>>>>
>>>> If you check you will see that just like -1 is negative, this matrix is
>>>> not positive definite.
>>>>
>>>> What you should be asking is how does one parameterize the positive
>>>> definite matrices in a
>>>> nice way to do nonlinear parameter estimation.
>>>>
>>>>
>>>>
>>>> Hi, Dr. Fournier. Thank you very much for your reply. Attached
>>>> is models that reflect the TPL code. At the moment, I have no clue about
>>>> why the covariance matrix is not positive definite.
>>>> Saang-Yoon
>>>>
>>>> On Monday, November 3, 2014 2:58:49 PM UTC-5, dave fournier wrote:
>>>>
>>>>> What makes you think the covariance matrix will be positive definite
>>>>> with your parameterization?
>>>>>
>>>>> On Sunday, November 2, 2014 5:49:50 PM UTC-8, Saang-Yoon wrote:
>>>>>>
>>>>>> Hi. There was no error in compile-link for the attached TPL file;
>>>>>> i.e., I got its executable file. However, I fail to get convergence
>>>>>> results. Would you mind checking the TPL?
>>>>>> Following are commands for runs.
>>>>>>
>>>>>> admb -r -s ssmbr3v4.tpl
>>>>>> ssmbr3v4 -ind simdataall2.dat -ainp ssmbr3v3.pin -phase 1 -noinit
>>>>>> ssmbr3v4 -ind simdataall2.dat -ainp ssmbr3v3.pin -phase 9 -noinit
>>>>>>
>>>>>> Thank you.
>>>>>> Saang-Yoon
>>>>>>
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