similar to: [Fwd: Re: R-help Digest, Vol 95, Issue 17]

For those issues with optimization methods (optim, optimx, and others) I see, a good percentage are because the objective function (or gradient if user-supplied) is mis-coded. However, an almost equal number are due to functions getting into overflow or underflow territory and yielding quantities that the optimization tools cannot handle (NA or Inf etc.) Two general approaches I find helpful: 1)

How about allowing underscore? (I believe WRE is silent on this, and I have not tried submitting a package with underscore in the title.) As I pointed out in my OP, _optim()_ works. And we have the advantage that we can distinguish package from function. The purpose of consistent editing is surely to provide the affordances that save us from needing extra documentation, as per Donald Norman's

Hendrik pointed out it was the parentheses that gave the complaint. Single quotes and no parentheses seem to satisfy R CMD check. Perhaps that needs to be in the WRE. However, I have for some time used the parentheses to distinguish functions from packages. optim() is a function, optimx a package. Is this something CRAN should be thinking about? I would argue greater benefit to users than title

> On 25 Apr 2015, at 13:11 , Prof J C Nash (U30A) <nashjc at uottawa.ca> wrote: > > Hendrik pointed out it was the parentheses that gave the complaint. > Single quotes and no parentheses seem to satisfy R CMD check. Perhaps > that needs to be in the WRE. Well, it is in ?toTitleCase: ...However, unknown technical terms will be capitalized unless they are single

On 24.04.2015 22:44, Ben Bolker wrote: > Prof J C Nash (U30A <nashjc <at> uottawa.ca> writes: > >> >> I was preparing a fix for a minor glitch in my optimx package and R CMD >> check gave an error that the title was not in title case. > > [snip] to make Gmane happy ... > >> I have found >> >> A Replacement and Extension of the

predict.warn() -- a function to display factor levels in new data for linear model prediction that do not exist in the estimating data. Date: 2005-8-24 From: John C. Nash (with thanks to Uwe Ligges for suggestions) nashjc at uottawa.ca Motivation: In computing predictions from a linear model using factors, it is possible to introduce new factor levels. This was encountered on a practical

There is also the OptimizeR project on R-forge http://r-forge.r-project.org/R/?group_id=395. Other related projects are there also, but I'll let their authors speak for themselves. Stefan Theussl did a good job in the Task View, but it is from last June, and it would be a monumental effort to keep up to date with all the work going on. We're "almost" ready to put some of our

Dear R users, I have been trying to understand what the Weights arguments is doing in the estimation of the parameters when using the Surreg function. I looked through the function's code but I am not sure if I got it or not. For example, if I inclue the Surv function in it: survreg(Surv(vector, status)~1,weights=vector2,dist="Weibull") will it try to maximize the likelihood with

There will be a meeting of the Ottawa Gatineau R Users Group on Monday November 10 from 4pm to 6pm. More details are provided below. Please pass this message along to friends you think may be interested. Paul Gilbert _________ Dear R friends: To get OGRUG going again I've reserved room DMS 6160 in the Desmarais Building of the University of Ottawa for 1600-1800 November 10. This is the

This is mainly a reminder to others developing R packages to be careful not to supply control list items that are not used by the called package. Optimx is a wrapper package that aims to provide a common syntax to a number of existing optimization packages. Recently in extending optimx package I inadvertently introduced a new control for optimx which is NOT in any of the wrapped optimization

I was preparing a fix for a minor glitch in my optimx package and R CMD check gave an error that the title was not in title case. It is A Replacement and Extension of the optim() Function R CMD check suggests the incorrect form A Replacement and Extension of the Optim() Function 'Writing R Extensions' suggests single quotes, i.e., A Replacement and Extension of the 'optim()'

Hi, everybody. I am working processing EEG data from 1000 pacients. I have a specific syntax to perform the Spectral Analysis and a loop to analyse all subjects. each subject data are in separate folders (P1, P2 P3...) My question is: in some cases, some errors can appear in one subject. I want to know if is possible to jump to the next subject and perform the same syntax , exibiting an error

Dear R users I have tried to install the optimx but met problems. I have gone to the website you suggested: https://r-forge.r-project.org/R/?group_id=395 and tried to install it with the following method: install.packages("optimx", repos="http://R-Forge.R-project.org") I have received the following information: package 'numDeriv' successfully unpacked and MD5

Dear R users When I use OPTIMX with BFGS, I've got the following error message. ----------------------------------------------------------------- > optimx(par=theta0, fn=obj.fy, gr=gr.fy, method="BFGS") Error: Gradient function might be wrong - check it! ----------------------------------------------------------------- So, I checked and checked my gradient function line by

With some chagrin after spending a couple of hours trying to debug a script, I realized I had typed in something like ans<-optimx(start, myfn, mygr, lower<-lo, upper=up) that is, the "<-" rather than "=". The outcome on my machine was a non-obvious error several layers deep in the call stack. For info, optim() seems to stop much more quickly. The error is

After some thought, I decided r-devel was probably the best of the R lists for this item. Do feel free to share, as the purpose is to improve documentation and identify potential issues. John Nash The R Consortium has awarded some modest funding for "histoRicalg", a project to document and transfer knowledge of some older algorithms used by R and by other computational systems. These

Dear R users When I use OPTIM with BFGS, I've got a significant result without an error message. However, when I use OPTIMX with BFGS( or spg), I've got the following an error message. ---------------------------------------------------------------------------------------------------- > optimx(par=theta0, fn=obj.fy, gr=gr.fy, method="BFGS", >

Ben Bolker pointed out in a response about max. likelihood estimation that parameter scaling is not available in nlminb On 02/03/2012 06:00 AM, r-help-request at r-project.org wrote: > * if you were using one of the optimizing methods from optim() (rather > than nlminb), e.g. L-BFGS-B, I would suggest you try using parscale to > rescale the parameters to have approximately equal

Dear R users I am trying to use OPTIMX(OPTIM) for nonlinear optimization. There is no error in my code but the results are so weird (see below). When I ran via OPTIM, the results are that Initial values are that theta0 = 0.6 1.6 0.6 1.6 0.7. (In fact true vales are 0.5,1.0,0.8,1.2, 0.6.) -------------------------------------------------------------------------------------------- >

I'll not copy all the previous material on this thread to avoid overload. The summary is that all the methods Spencer has tried have some issues. The bad news: This is not uncommon with optimization methods, in part because the problems are "hard", in part because getting them implemented and linked to an interfacing approach like R is very tedious and prone to omissions and