[R] Non linear modeling

Spencer Graves spencer.graves at pdf.com
Fri Mar 18 20:35:38 CET 2005


      What do you want to minimize?  Can you write a function to compute 
eps given x, y, and a?  Given that, you can then write another function 
to compute the objective function you want to minimize.  If "a" is a 
scalar, compute the objective function for a range of values of "a" and 
plot.  If you want numerical precision, read the help file for "optim", 
work the examples until you understand enough to see how to feed your 
objective function with a starting value to "optim". 

      If you still can't figure it out, please make an attempt, then 
read the posting guide "http://www.R-project.org/posting-guide.html", 
and prepare a follow-up question as needed.  (In a discussion on and off 
this list earlier this week, several people confirmed that they had 
solved many problems following this posting guide.  It may not be as 
good as Polya's famous "How to Solve It", but it's pretty good.)

      hope this helps. 
      spencer graves

Angelo Secchi wrote:

>You are right. eps in my model is not a parameter but the error term.
>Also the linearization doesn't solve the problem, since sometimes you
>cannot take logs. Any other ideas?
>Thanks
>
>
>On Fri, 18 Mar 2005 11:21:12 -0500
>"Liaw, Andy" <andy_liaw at merck.com> wrote:
>
>  
>
>>That's treating eps as a parameter in the model.  If I read your question
>>right, that's not what you want.  
>>
>>Andy
>>
>>    
>>
>>>From: ronggui [mailto:0034058 at fudan.edu.cn] 
>>>
>>>then is the nls function can deal the problem as Guillaume 
>>>STORCHI mentioned in the last post? [X<-nls(y~x+exp(a*x)*eps, 
>>>data=,start=list(a=,eps=))]
>>>or just can solve the problem as:log(y-x) = a*x + e?
>>>
>>>
>>>
>>>On Fri, 18 Mar 2005 08:56:38 -0500
>>>"Liaw, Andy" <andy_liaw at merck.com> wrote:
>>>
>>>      
>>>
>>>>AFAIK most model fitting techniques will only deal with 
>>>>        
>>>>
>>>additive errors, not
>>>      
>>>
>>>>multiplicative ones.  You might want to try fitting:
>>>>
>>>>log(y-x) = a*x + e
>>>>
>>>>which is linear.
>>>>
>>>>Andy
>>>>
>>>>        
>>>>
>>>>>From: Angelo Secchi
>>>>>
>>>>>Hi,
>>>>>is there a way  in R to fit a non linear model like
>>>>>
>>>>>y=x+exp(a*x)*eps
>>>>>
>>>>>where a is the parameter and eps is the error term? 
>>>>>Thanks
>>>>>Angelo
>>>>>
>>>>>______________________________________________
>>>>>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
>>>>>
>>>>>
>>>>>
>>>>>          
>>>>>
>>>>______________________________________________
>>>>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
>>>
>>>
>>>
>>>      
>>>
>>
>>------------------------------------------------------------------------------
>>Notice:  This e-mail message, together with any attachment...{{dropped}}
>>    
>>
>
>______________________________________________
>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
>  
>




More information about the R-help mailing list