Refer to the CRAN "Optimization" task view, please. That is a much more
appropriate place to begin than posting a query here.

All numerical optimizers only produce local optima.

-- Bert

On Thu, Nov 10, 2011 at 11:24 AM, Dimitri Liakhovitski <
dimitri.liakhovit...@gmail.com> wrote:

> Just to add:
>
> I also experimented with the starting parameters (par) under optim,
> especially with the second one. I tried 1, 10, 100, 1000, etc.
> When I tried 100,000,000 then I got a somewhat better solution (but
> still not as good as in Excel). However, under message it said:
>
> "ERROR: ABNORMAL_TERMINATION_IN_LNSRCH"
>
> Dimitri
>
> On Thu, Nov 10, 2011 at 1:50 PM, Dimitri Liakhovitski
> <dimitri.liakhovit...@gmail.com> wrote:
> > Hello!
> >
> > I am trying to create an R optimization routine for a task that's
> > currently being done using Excel (lots of tables, formulas, and
> > Solver).
> > However, otpim seems to be finding a local minimum.
> > Example data, functions, and comparison with the solution found in
> > Excel are below.
> > I am not experienced in optimizations so thanks a lot for your advice!
> > Dimitri
> >
> > ### 2 Inputs:
> >
> IV<-data.frame(IV=c(0,6672895.687,13345791.37,20018687.06,26691582.75,33364478.44,40037374.12,46710269.81,53383165.5,
> 60056061.18,66728956.87,73401852.56,80074748.24,86747643.93
> ,93420539.62,100093435.3,106766331,113439226.7,120112122.4,126785018.1,133457913.7,140130809.4,146803705.1,153476600.8,160149496.5,166822392.2,173495287.9,180168183.5,186841079.2,193513974.9,200186870.6))
> > DV<-data.frame(DV=c(0,439.8839775,829.7360945
> ,1176.968757,1487.732038,1767.147276,2019.49499,2248.366401
> ,2456.78592,2647.310413,2822.109854,2983.033036,3131.661246,3269.352233,
> 3397.276321,3516.446162
> ,3627.741311,3731.928591,3829.679009,3921.581866,4008.156537,4089.862363,
> 4167.106955,4240.253215,4309.625263,4375.513474,4438.178766
> ,4497.856259,4554.75841,4609.077705,4660.988983))
> >
> > ## Function "transformIV" transforms a data frame column "IV" using
> > parameters .alpha & .beta:
> > ## It returns a data frame column IV_transf:
> > transformIV = function(.alpha,.beta) {
> >  IV_transf <- as.data.frame(1 - (1/exp((IV/.beta)^.alpha)))
> >  return(IV_transf)
> > }
> >
> > ### Function "mysum" calculates the sum of absolute residuals after a
> > regression with a single predictor:
> > mysum<- function(myIV,myDV){
> >  regr<-lm(myDV[[1]] ~ 0 + myIV[[1]])
> >  mysum<-sum(abs(regr$resid))
> >  return(mysum)
> > }
> >
> > ### Function to be optimized;
> > ### param is a vector of 2 values (.alpha and .beta)
> > myfunc <- function(param){
> >  myalpha<-param[1]
> >  mybeta<-param[2]
> >  IVtransf<-transformIV(myalpha, mybeta)
> >  sumofdevs<-mysum(myIV=IVtransf,myDV=DV)
> >  return(sumofdevs)
> > }
> >
> > # Optimizing using optim:
> > myopt <- optim(fn=myfunc, par=c(0.1,max(IV)), method="L-BFGS-B", lower=0)
> > (myopt)
> > myfunc(myopt$par)
> > ## Comparing this solution to Excel Solver solution:
> > myfunc(c(0.888452533990788,94812732.0897449))
> >
> > --
> > Dimitri Liakhovitski
> > marketfusionanalytics.com
> >
>
>
>
> --
> Dimitri Liakhovitski
> marketfusionanalytics.com
>
> ______________________________________________
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>



-- 

Bert Gunter
Genentech Nonclinical Biostatistics

Internal Contact Info:
Phone: 467-7374
Website:
http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm

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