similar to: minimizing a numerical integration

Dear all, I tried running the following syntax but it keeps running for about 4 hours and then i got the following errors: Error in if (is.na(f0$objective)) { : argument is of length zero In addition: Warning message: In is.na(f0$objective) : is.na() applied to non-(list or vector) of type 'NULL' Here is the syntax itself: library('nloptr') library('pracma') #

Dear all, The attached code is supposed to minimize a numerical integration subject to a non linear constraint. The code runs for 2 days& more without giving an output. Also, when i change the value of "m<-100" to "m<-1" it gives an output in areasonable period but with a message " maximum number of iterations in romberg has been reached". I need to : 1-

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

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

I have a complex function that I want to maximize (I have multiplied this function by -1 so that it becomes a minimization problem in the code below). This function has two equality constraints. I get the programs to run but the answer isn't correct because, when it does converge, at least one of the constraints is violated. Any suggestions? Code below Violated constraint (an easy check):

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.

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-help members Since this morning (5/2/2025), I get an error when I try to load optimx package. I solve it and I send my solution but if someone has a better idea or understand what's happened, I will be most happy to know. MacOSX 15.3 R 4.4.2 nlopt installed using brew install nlopt Here are the steps to produce the error and a solution to solve it. Some parts are in French. I

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.

Hello Christofer, Just writing with a detailed follow-up. Attached is a script I was able to get running with a bit of work. I did not include the script in the ext of this email. It is only attached. Optimization Progress We were initially aiming to solve the dual-slope constrained ordinal model using nloptr's SLSQP algorithm (NLOPT_LD_SLSQP), since it supports: ? Box constraints (per-?

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

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

try to Rcmdr package install? but the last message show me error, The downloaded source packages are in ??? ?/tmp/RtmpKic0qw/downloaded_packages? Warning messages: 1: In install.packages() : ? installation of package ?nloptr? had non-zero exit status 2: In install.packages() : ? installation of package ?lme4? had non-zero exit status 3: In install.packages() : ? installation of package

Dear R-devel, Recently I ran into trouble installing two separate packages, nloptr and ncdf4, both due to the same issue: they have scripts that have the shebang `#! /bin/sh', but have bashisms in them, i.e. non-POSIX-compliant bash scripts. I use dash [1] as my shell environment, since it's about 4x as fast as bash. It looks like it's recently also become the default shell for

Thanks for all your great answers. The app I?m working on is indeed an exploratory data analysis tool for gene expression, which requires a bunch of bioconductor packages. I guess for now, my best solution is to divide my app into modules and load/unload packages as the user switch from one module to another. This brought me another question: it seems that unload package with the

Muy buenas, Tengo la siguiente duda/problema, He optimizado con éxito un problema de este tipo: \sum f(x_i) donde f es una curva exponencial (función no lineal) sujeto a: a_i < x_i < b_i y \sum f(x_i) < Presupuesto Vamos, es repartir un presupuesto forzando a que inviertas como poco a_i y como mucho b_i para cada i Esto lo hecho correctamente usando el paquete:

Thanks Bert. But everyone on that forum wants to use finance tools rather than general optimization stuff! And I am not optimizing a traditional Markowitz mean-variance problem. Plus, smarter people here. :-) > On May 3, 2018, at 3:01 PM, Bert Gunter <bgunter.4567 at gmail.com> wrote: > > You can't -- at least as I read the docs for ?optim (but I'm pretty > ignorant

On 6 June 2023 at 23:33, Johan Andresen wrote: | Cheers - my response mixes up the order of things: | | The suggested apt way INSTALLED INTERFLEX nicely. Lesson learned: install | dependencies from apt if a package/library isn't in apt search. | | Yes I also tried install.packages('interflex'). RStudio console complained | about the same packages like this: | ERROR: dependency

Hi, am very new to R and I've written an optim function, but can't get it to work least.squares.fitter<-function(start.params,gr,low.constraints,high.constraints,model.one.stepper,data,scale,ploton=F) { result<-optim(par=start.params,method=c('Nelder-Mead'),fn=least.squares.fit,lower=low.constraints,upper=high.constraints,data=data,scale=scale,ploton=ploton)

During installation of a package, Makevars/Makefile in src/ is processed. I've always considered the purpose of this for compiling native code. Is that it's solely purpose, or is it alright to use it also for non-code compilation purposes, e.g. building inst/ subdirectories on the fly? If not, are there other means to create non-static inst/ subdirectories during installation? The