[ADMB Users] NLS example

[dave fournier]

I'm sure R users would be interested in this!



This example runs beautifully with

     -crit 1.e-10

It is part of some excel bashing on the R list in

https://stat.ethz.ch/pipermail/r-help/2013-February/347920.html

there is na example description

http://www.itl.nist.gov/div898/strd/nls/data/mgh09.shtml

Wonder how nls does in R

tpl,dat and pin files are attached.


> On 13-02-22 02:40 PM, dave fournier wrote:
>> On 13-02-22 11:33 AM, Ben Bolker wrote:
>>
>> I agree that backwards compatibility is important.
>>   We could go back to having a robust flag which would
>> activate the options.   I think a lot of the existing trouble with this
>> data
>> set is with
>> the bounds on tmpL and u.
>> That was probably why sometimes -noinit would crash
>> There will always be a new data set
>> that will break something.
>    Of course.  I just don't want to break *old* data sets, or at least I
> want to allow people to be able to un-break things if the default
> settings break them ...
>
>>
>>> On 13-02-22 02:28 PM, dave fournier wrote:
>>>> On 13-02-22 07:26 AM, Ben Bolker wrote:
>>>>
>>>> Then I reran the model and the variances got stuck near 0.
>>>> a small penalty for a while fixes that.  So I think a model
>>>> something like this would be good.
>>>>
>>>>
>>>>>       Hans, can you put this version of the glmmADMB TPL file up on
>>>>> the SVN
>>>>> repository so the buildbot will build it?  It includes a beta-binomial
>>>>> likelihood option and Dave's latest NB tweak ...
>>>>>      (I probably do have write access to the SVN repository if I could
>>>>> figure it out, but I only have to do this a few times a year so I'm
>>>>> being lazy ...)
>>>>>
>>>>>      thanks
>>>>>        Ben
>>>     Thanks, Dave.  I will look this over and try to understand the bits
>>> and pieces.  If possible I would like to try to make the upper bound on
>>> the random effects values into a user-settable parameter (controlled by
>>> admb.opts/admbControl) ...  Now that we have code that people are using,
>>> I worry a lot about making backward-incompatible changes (i.e. this code
>>> makes some models run OK, but breaks others that are out there in the
>>> wild somewhere).
>>>
>>>     cheers
>>>       Ben
>>>

-------------- next part --------------
DATA_SECTION
  init_int n
  init_matrix data(1,n,1,2)
  vector x
  vector Y
 !! x=column(data,2);
 !! Y=column(data,1);
PARAMETER_SECTION
  init_vector b(1,4)
   objective_function_value f
PROCEDURE_SECTION
  dvar_vector num=b(1)*(square(x)+x*b(2));
  dvar_vector den=square(x)+x*b(3)+b(4);
  dvar_vector predY= elem_div(num,den);
  f=norm2(Y-predY);
-------------- next part --------------
# starting values 1
 25 39 41.5 39
   
    
      
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