[R] question on "optim"

[Paulo Barata]

Dear R-list members,

I am using R 2.11.1 on Windows XP. When I try to install package
"optimx" through the GUI menu Packages / Install packages, this
package does not appear in the list that opens up (chosen from the
Austria CRAN site). The package is listed on Austria's CRAN web
page, but today (8 September 2010) it does not show in the list
obtained through the menu.

Thank you.

Paulo Barata

(Rio de Janeiro - Brazil)

------------------------------------------------------------------
------------------------------------------------------------------


On 8/9/2010 11:01, Ravi Varadhan wrote:
> Hi Nan,
>
> You can take a look at the "optimx" package on CRAN.  John Nash and I wrote
> this package to help lay and sophisticated users alike.  This package
> unifies various optimization algorithms in R for smooth, box-constrained
> optimization. It has features for checking objective function, gradient (and
> hessian) specifications.  It checks for potential problems due to poor
> scaling; checks feasibility of starting values.  It provides diagnostics
> (KKT conditions) on whether or not a local optimum has been located.  It
> also allows the user to run various optimization algorithms in one simple
> call, which is essentially identical to "optim" call. This feature can be
> especially useful for developers to benchmark different algorithms and
> choose the best one for their class of problems.
>
> http://cran.r-project.org/web/packages/optimx/index.html
>
> Ravi.
>
> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On
> Behalf Of Hey Sky
> Sent: Tuesday, September 07, 2010 2:48 PM
> To: Ben Bolker; r-help at stat.math.ethz.ch
> Subject: Re: [R] question on "optim"
>
> thanks. Ben
>
> after read your email, I realized the initial value of w[5]=0 is a stupid
> mistake. and I have changed it. but I am sorry I cannot reproduce the
> result,
> convergence, as you get. the error message is<non-finite finite difference
> value [12]>. any suggestion about it?
>
> and could you plz recommend some R books on optimization, such as tips for
> setup
> gradient and others, or common mistakes?  thanks
>
> Nan
>
>
>
>
>
>
>
> ----- Original Message ----
> From: Ben Bolker<bbolker at gmail.com>
> To: r-help at stat.math.ethz.ch
> Sent: Tue, September 7, 2010 11:15:43 AM
> Subject: Re: [R] question on"optim"
>
> Hey Sky<heyskywalker<at>  yahoo.com>  writes:
>
>> I do not know how to describe my question. I am a new user for R and
>> write the
>> following code for a dynamic labor economics model and use OPTIM to get
>> optimizations and parameter values. the following code does not work due
> to
>> the equation:
>>
>>     wden[,i]<-dnorm((1-regw[,i])/w[5])/w[5]
>>
>> where w[5] is one of the parameters (together with vector a, b and other
>> elements in vector w) need to be estimated. if I
>>   delete the w[5] from the upper
>> equation. that is:
>>
>>   wden[,i]<-dnorm(1-regw[,i])
>>
>> optim will give me the estimated parameters.
>
>    Thank you for the reproducible example!
>
>    The problem is that you are setting the initial value of w[5]
> to zero, and then trying to divide by it ...
>
>    I find that
>
>
> guess<-rep(0,times=npar)
> guess[16]<- 1
>
> system.time(r1<-optim(guess,myfunc1,data=mydata, method="BFGS",hessian=TRUE,
>                        control=list(trace=TRUE)))
>
> seems to work OK (I have no idea if the answers are sensible are not ...)
>
> If you're going to be doing a lot of this it might be wise to see
> if you can specify the gradient of your objective function for R --
> it will speed up and stabilize the fitting considerably.
>
>    By the way, you should be careful with this function: if we try
> this with Nelder-Mead instead, it appears to head to a set of
> parameters that lead to some sort of singularity in the objective
> function:
>
> system.time(r2<-optim(guess,myfunc1,data=mydata,
>     method="Nelder-Mead",hessian=FALSE,
>                        control=list(trace=TRUE,maxit=5000)))
>
> ## still thinks it hasn't converged, but objective function is
> ##   much smaller
>
> ## plot 'slice' through objective space where 0 corresponds to
> ##  fit-1 parameters and 1 corresponds to fit-2 parameters;
> ## adapted from emdbook::calcslice
> range<- seq(-0.1,1.1,length=400)
> slicep<- seq(range[1], range[2], length = 400)
> slicepars<- t(sapply(slicep, function(x) (1 - x) * r1$par +  x * r2$par))
> v<- apply(slicepars, 1, myfunc1)
> plot(range,v,type="l")
>
>
>    Ideally, you should be able to look at the parameters of fit #2
> and figure out (a) what the result means in terms of labor economics
> and (b) how to keep the objective function from going there, or at
> least identifying when it does.
>
>    Ben Bolker
>
> ______________________________________________
> R-help at r-project.org 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 r-project.org 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 r-project.org 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.
>
>