[R] nonlinear least squares fitting Trust-Region"

Spencer Graves spencer.graves at pdf.com
Sun Sep 3 02:41:21 CEST 2006


Hi, Ravi: 

      Thanks for the reference.  I believe that Bates' thesis adviser 
was Donald G. Watts.  I'm not certain, but I think Watts had a 
connection with the University of Wisconsin, but I'm not certain of 
that.  Maybe someone else will correct / confirm or amplify on this. 

      Best Wishes,
      Spencer

RAVI VARADHAN wrote:
> I think the idea of parameter and intrinsic nonlinearity is due to Beale (JRSSB 1960).  Was he Doug Bates' thesis advisor?
>
> Ravi.
>
> ----- Original Message -----
> From: Spencer Graves <spencer.graves at pdf.com>
> Date: Saturday, September 2, 2006 2:05 pm
> Subject: Re: [R] nonlinear least squares fitting Trust-Region"
> To: RAVI VARADHAN <rvaradhan at jhmi.edu>
> Cc: Prof Brian Ripley <ripley at stats.ox.ac.uk>, Martin Ivanov <tramni at abv.bg>, r-help at stat.math.ethz.ch
>
>   
>>      May I also suggest Bates and Watts (1988) Nonlinear 
>> Regression 
>> Analysis and Its Applications (Wiley).  This book carefully 
>> explains the 
>> difference between "parameter effects" and "intrinsic" curvature 
>> in 
>> non-linear fitting. I don't know if this idea was original with 
>> Bates or 
>> Watts, but I believe that Bates' PhD dissertation made important, 
>> original contributions to our understanding of it -- and it helped 
>> get 
>> him the faculty position in Statistics at the University of 
>> Wisconsin, 
>> where he still is.  Bates is also a leading contributor to R. 
>>
>>      hope this helps. 
>>      spencer graves
>>
>> RAVI VARADHAN wrote:
>>     
>>> As suggested by Prof. Ripley, you should read a good book in the 
>>>       
>> optimization area.  One that I would highly recommend is the book 
>> by Dennis and Schnabel (1983) - Numerical methods for 
>> unconstrained optimization, which does a great job of explaining 
>> both "line-search" and "trust-region" approaches for achieving 
>> globally-convergent versions of a fast numerical scheme such as 
>> Gauss-Newton.
>>     
>>> Best,
>>> Ravi.
>>>
>>> ----- Original Message -----
>>> From: Prof Brian Ripley <ripley at stats.ox.ac.uk>
>>> Date: Saturday, September 2, 2006 5:51 am
>>> Subject: Re: [R] nonlinear least squares fitting Trust-Region"
>>> To: Martin Ivanov <tramni at abv.bg>
>>> Cc: r-help at stat.math.ethz.ch
>>>
>>>   
>>>       
>>>> I believe people (including me) did not reply because you 
>>>>         
>> appeared 
>>     
>>>> not to 
>>>> have done your homework.  The help page for ?nls _does_ have a 
>>>> reference 
>>>> to the 'port' documentation, and RSiteSearch("trust region") is 
>>>> informative and leads to an R package that does trust-region 
>>>> optimization.  
>>>> (So would looking in the R FAQ.)
>>>>
>>>> You say:
>>>>
>>>>     
>>>>         
>>>>> Since I am not an expert in the field of optimization, I am 
>>>>>           
>> just 
>>     
>>>>> conforming to what matlab documentation
>>>>>       
>>>>>           
>>>> Please note that some of the R developers are really expert in 
>>>> that area, 
>>>> and their advice (in the R documentation) should be taken as 
>>>> seriously as 
>>>> that in some commercial package that is merely commenting about 
>>>> the very 
>>>> sparse choice it offers.  Or if R is not in your personal trust 
>>>> region, 
>>>> just use 'matlab'.
>>>>
>>>> Please
>>>>
>>>> 1) do not shout at your helpers: using all caps is regarded as 
>>>> shouting.
>>>> 2) study and follow the posting guide.  People are much more 
>>>> likely to 
>>>> help you if you demonstrate you have made efforts to help yourself.
>>>>
>>>> 3) read the literature.  The R FAQ leads to books that cover 
>>>> fitting 
>>>> non-linear models in S/R in considerable detail.
>>>>
>>>>
>>>> On Sat, 2 Sep 2006, Martin Ivanov wrote:
>>>>
>>>>     
>>>>         
>>>>> Dear Mr Graves,
>>>>>       
>>>>> Thank you very much for your response. Nobody else from this 
>>>>>       
>>>>>           
>>>> mailing 
>>>>     
>>>>         
>>>>> list ventured to reply to me for the two weeks since I posted 
>>>>>           
>> my 
>>     
>>>>> question. "nlminb" and "optim" are just optimization 
>>>>>           
>> procedures. 
>>     
>>>>>       
>>>>>           
>>>> What I 
>>>>     
>>>>         
>>>>> need is not just optimization, but a nonlinear CURVE FITTING 
>>>>>       
>>>>>           
>>>> procedure.
>>>> Which is just optimization: usually by least squares (although 
>>>>         
>> you 
>>     
>>>> have 
>>>> not actually specified that and there are better modern 
>>>> statistical 
>>>> ideas).
>>>>
>>>>     
>>>>         
>>>>> If there is some way to perform nonlinear curve fitting with 
>>>>>           
>> the 
>>     
>>>>> "Trust-Region" algorithm using any of these functions, I would 
>>>>>       
>>>>>           
>>>> me much 
>>>>     
>>>>         
>>>>> obliged to you if you suggest to me how to achieve that. You 
>>>>>       
>>>>>           
>>>> asked me 
>>>>     
>>>>         
>>>>> why I do not want Gauss-Newton. Since I am not an expert in 
>>>>>           
>> the 
>>     
>>>>>       
>>>>>           
>>>> field of 
>>>>     
>>>>         
>>>>> optimization, I am just conforming to what matlab 
>>>>>           
>> documentation 
>>     
>>>>> suggests, namely: "Algorithm used for the fitting procedure: 
>>>>> Trust-Region -- This is the default algorithm and must be used 
>>>>>       
>>>>>           
>>>> if you 
>>>>     
>>>>         
>>>>> specify coefficient constraints. Levenberg-Marquardt -- If the 
>>>>> trust-region algorithm does not produce a reasonable fit, and 
>>>>>       
>>>>>           
>>>> you do not 
>>>>     
>>>>         
>>>>> have coefficient constraints, you should try the Levenberg-
>>>>>       
>>>>>           
>>>> Marquardt 
>>>>     
>>>>         
>>>>> algorithm. Gauss-Newton --THIS ALGORITHM IS POTENTIALLY FASTER 
>>>>>       
>>>>>           
>>>> THAN THE 
>>>>     
>>>>         
>>>>> OTHER ALGORITHMS, BUT IT ASSUMES THAT THE RESIDUALS ARE CLOSE 
>>>>>           
>> TO 
>>     
>>>>>       
>>>>>           
>>>> ZERO. 
>>>>     
>>>>         
>>>>> IT IS INCLUDED FOR PEDAGOGICAL REASONS AND SHOULD BE THE LAST 
>>>>>       
>>>>>           
>>>> CHOICE FOR 
>>>>     
>>>>         
>>>>> MOST MODELS AND DATA SETS. I browsed some literature about the 
>>>>>       
>>>>>           
>>>> garchfit 
>>>>     
>>>>         
>>>>> function, but I did not see the "Trust-Region" algorithm there 
>>>>>       
>>>>>           
>>>> either: 
>>>>     
>>>>         
>>>>> algorithm = c("sqp", "nlminb", "lbfgsb", "nlminb+nm", 
>>>>>       
>>>>>           
>>>> "lbfgsb+nm"), 
>>>>     
>>>>         
>>>>> control = list(), title = NULL, description = NULL, ...)
>>>>>
>>>>> Thank you for your attention. I am looking forward to your reply.
>>>>> Regards,
>>>>> Martin
>>>>>
>>>>> ---------------------------------------------------------------
>>>>>           
>> --
>>     
>>>>> vbox7.com - ??????? ????? ???????!
>>>>>
>>>>> ______________________________________________
>>>>> R-help at stat.math.ethz.ch mailing list
>>>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>>>> PLEASE do read the posting guide http://www.R-
>>>>>       
>>>>>           
>>>> project.org/posting-guide.html
>>>>     
>>>>         
>>>>> and provide commented, minimal, self-contained, reproducible code.
>>>>>
>>>>>       
>>>>>           
>>>> -- 
>>>> Brian D. Ripley,                  ripley at stats.ox.ac.uk
>>>> Professor of Applied Statistics,  
>>>>         
>> http://www.stats.ox.ac.uk/~ripley/>> University of Oxford,         
>>    Tel:  +44 1865 272861 (self)
>>     
>>>> 1 South Parks Road,                     +44 1865 272866 (PA)
>>>> Oxford OX1 3TG, UK                Fax:  +44 1865 272595
>>>>
>>>> ______________________________________________
>>>> R-help at stat.math.ethz.ch mailing list
>>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>>> PLEASE do read the posting guide http://www.R-
>>>>         
>> project.org/posting-
>>     
>>>> guide.htmland provide commented, minimal, self-contained, 
>>>> reproducible code.
>>>>
>>>>     
>>>>         
>>> ______________________________________________
>>> R-help at stat.math.ethz.ch mailing list
>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEASE do read the posting guide http://www.R-
>>>       
>> project.org/posting-guide.html
>>     
>>> and provide commented, minimal, self-contained, reproducible code.
>>>   
>>>       
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>



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