Re: [R] question on "optim"

Paulo Barata Wed, 08 Sep 2010 13:27:34 -0700


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)

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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-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Hey Sky
Sent: Tuesday, September 07, 2010 2:48 PM
To: Ben Bolker; r-h...@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<bbol...@gmail.com>
To: r-h...@stat.math.ethz.ch
Sent: Tue, September 7, 2010 11:15:43 AM
Subject: Re: [R] question on&quot;optim&quot;

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

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______________________________________________
R-help@r-project.org mailing list
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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.

______________________________________________
R-help@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@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.

Re: [R] question on "optim"

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