similar to: Error when loading optimx package and a solution

Hi, That looks like the dependency on nlopt for nloptr (used by several of the solvers) was somehow missing. There is SUPPOSED to be a check of what is installed and a warning issued, but possibly one got missed. Even some base packages do sometimes need the external libraries manually installed, and I find I'm doing that after various OS updates or resets when the long term support runs out.

I can't install rugarch package because installation of nloptr package fails . I use opensuse 12.3 # uname -a Linux candide 3.7.10-1.11-desktop #1 SMP PREEMPT Thu May 16 20:27:27 UTC 2013 (adf31bb) x86_64 x86_64 x86_64 GNU/Linux my gcc version is 4.8.1 I compiled and installed R 3.01 . then I tried to install rugarch package but it fails because it can't install depended package nloptr.

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

Hi, Mark et al.: Thanks, Mark. Three comments: 1. Rvmmin was one of the methods I tried after Ravi directed me to optimx. It returned NAs for essentially everything. See my email of this subject stamped 4:43 PM Central time = 21:43 UTC. 2. It would be interesting to know if the current algorithm behind optim and optimx with

Hello: The development version of Ecdat on R-Forge contains a vignette in which optim(?, method=?L-BFGS-B?) stops with an error message while violating the lower bound. To see all the details, try the following: install.packages("Ecdat", repos="http://R-Forge.R-project.org") Then do "help(pac=Ecdat)" -> "User guides, package

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", >

Dear R-er, For a non-linear optimisation, I used optim() with BFGS method but it stopped regularly before to reach a true mimimum. It was not a problem with limit of iterations, just a local minimum. I was able sometimes to reach better minimum using several rounds of optim(). Then I moved to optimx() to do the different optim rounds automatically using "Nelder-Mead" and

While working on 'random walk' applications, I got interested in optimizing noisy objective functions. As an (artificial) example, the following is the Rosenbrock function, where Gaussian noise of standard deviation `sd = 0.01` is added to the function value. fn <- function(x) (1+rnorm(1, sd=0.01)) * adagio::fnRosenbrock(x) To smooth out the noise, define another

Hi Reuben, I am puzzled to note that the gradient check in "optimx" does not work for you. Can you send me a reproducible example so that I can figure this out? John - I think the best solution for now is to issue a "warning" rather than an error message, when the numerical gradient is not sufficiently close to the user-specified gradient. Best, Ravi.

Hi, I try to make my first package? The HelloWorld.R file is: #### HelloWorld.R #### #' showHello est une fonction R permettant d'afficher le message #' "Hello World!" sur la console. #' @title la fonction showHello() showHello <-function(){ cat("Hello World!\n") } I use the following procedure to get the tar: # set the working directory where the file is

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

Have you tried "optimx" package that John Nash and I wrote? The main purpose is to be able to readily compare multiple optimizers on a particular class of problems and see which one seems to do the best. It doesn't include nloptr, but most other optimizers are there. Ravi ________________________________________ From: R-devel <r-devel-bounces at r-project.org> on behalf of

Dear all, I am a new user to R and I am using pracma and nloptr libraries to minimize a numerical integration subject to a single constraint . The integrand itself is somehow a complicated function of x and y that is computed through several steps. i formulated the integrand in a separate function called f which is a function of x &y. I want to find the optimal value of x such that the

Hi Gregg, Below I try to address 1) The sum constraint would apply for each set ?? and ?? i.e. sum(??) = sum(??) = 1.60 2) Just like 1) the lower and upper bounds will be applied for individual set i.e. individual elements of ?? are subject to lower = c(1, -1, 0) and upper = c(2, 1, 1) and individual elements of ?? are subject to lower = c(1, -1, 0) and upper = c(2, 1, 1) I hope that I am

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

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.) -------------------------------------------------------------------------------------------- >

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

Prof Nash, Prof Galanos Is it possible to use a generic code stub in front of packages that use optimx to improve optimx use or curtail it according to the requirements? Best Regards Amit +91 7899381263 ________________________________________________________________________ Please request Skype as available 5th Year FPM (Ph.D.) in Finance and Accounting Area Indian Institute

Dear all, this is my first time, and just begin to use R. But I've a question about optimization using optimx library. It could sound stupid by I'm a bit affraid with the problem, because anything I try, anything Error. The procedure was: optimx(par="10,71,1",fn=(Prey*Provisioning)/Risk, control=list("maximize)) well the problem lies in the initial value parameters, again