similar to: Two Questions on R (call by reference and pre-compilation)

Hi, I have been brought back to the "R-Side" from MatLab. I have used R in graduate econometrics but only for statistics and regression (linear and nonlinear). But now I need to run general nonlinear optimization. I know about the add-in quadprog but my problem is not QP. My problem is a general nonlinear (obj funct) with linear constraints.I know about the "ms" and

Hi, In my memory, "<<-" means assigning via a pointer or alias. But this is not officially defined in "R Language Definition". Could anybody help for the clarification? Thank you very much! Bests, Ruihong

Hi there, I have a piece of Matlab code I use to optimise a trding strategy. If there are any Matlab/R specialists out there, I would appreciate your help in doing the exact same optimisation in R. I suspect I would use nlm() in R but am not sure where to define my constraints. I have attached my Matlab code below for reference. Many thanks. Constraints function [c,ceq]=TriskellConstraints(X)

Dear all R users, I am wondering if there are any function for Constraint optimization in R. Especially i am looking for a R - equivalent of "fmincon" function in MATLAB. Thanks and regards, Arun [[alternative HTML version deleted]]

Hi, I'm using the Sweave and I would like include codes of the R in my LaTeX file. I extracts the R code with Stangle (), whose name is Relatorio.R but I can't include it in the Latex file as an appendix. Suggests? Thanks, -------------------------------------- Silvano Cesar da Costa Departamento de Estat?stica Universidade Estadual de Londrina Fone: 3371-4346

Hi, I need to solve an optimization problem in R having linear objective function and quadratic constraints(number of variables is around 80). What are the possible choices to do this in R. optim() function only allows box constrained problems. Is it possible in nlm()? Or please tell me if there is any other routine. Thanks Amit

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Hi Duncan, Thanks for your comment, I agree with that. But, how it can be justified that an Optimizer gives a result which is inferior to the starting value? At most, resulting value can remain at the same level, isnt it? On Fri, 28 Mar 2025 at 14:34, Duncan Murdoch <murdoch.duncan at gmail.com> wrote: > I haven't run your code, but since Kendall correlation is based on >

I haven't run your code, but since Kendall correlation is based on ranks, your Fn is probably locally constant with jumps when the ranks change. That's a really hard kind of function to maximize, and the algorithm used by fmincon is not appropriate to do it. Sorry, but I don't know if there is an R function that can do constrained discrete maximization. Duncan Murdoch On

?s 19:36 de 27/03/2025, Daniel Lobo escreveu: > My code is to minimize the objective function > > therefore, shouldnt I expect that > > StartingValue = c(0.12, 0.04, 0.07, 0.03, 0.06, 0.07, 0.07, 0.04, 0.09, > 0.08, 0.02, 0.02, 0.03, 0.06, 0.02, 0, 0.07, 0.05, 0.02, 0.02, 0.02) > Fn(q1$par) < Fn(StartingValue) > ## FALSE > > Below is the corrected code that can

Dear all, I am looking for a R-function that performs nonlinear constraint optimization (where the objective function and the constraints are allowed to be nonlinear). More specifically, I am trying to figure out whether there is an equivalent function of NAG fortran library' "E04UCF" or matlab's "fmincon" in R. Any help is greatly appreciated. Thank you, Sunduz

My code is to minimize the objective function therefore, shouldnt I expect that StartingValue = c(0.12, 0.04, 0.07, 0.03, 0.06, 0.07, 0.07, 0.04, 0.09, 0.08, 0.02, 0.02, 0.03, 0.06, 0.02, 0, 0.07, 0.05, 0.02, 0.02, 0.02) Fn(q1$par) < Fn(StartingValue) ## FALSE Below is the corrected code that can be reproduced: MyDat = structure(list(c(50L, 0L, 0L, 50L, 75L, 100L, 50L, 0L, 50L, 0L, 25L,

?s 13:59 de 28/03/2025, Daniel Lobo escreveu: > Hi Duncan, > > Thanks for your comment, I agree with that. > > But, how it can be justified that an Optimizer gives a result which is > inferior to the starting value? At most, resulting value can remain at the > same level, isnt it? > > On Fri, 28 Mar 2025 at 14:34, Duncan Murdoch <murdoch.duncan at gmail.com>

Hi, I have below minimization problem MyDat = structure(list(c(50L, 0L, 0L, 50L, 75L, 100L, 50L, 0L, 50L, 0L, 25L, 50L, 50L, 75L, 75L, 75L, 0L, 75L, 75L, 75L, 0L, 25L, 75L, 75L, 0L, 75L, 100L, 0L, 25L, 100L), c(75L, 0L, 0L, 50L, 100L, 50L, 75L, 75L, 100L, 25L, 0L, 25L, 100L, 0L, 50L, 0L, 25L, 25L, 100L, 75L, 0L, 0L, 0L, 50L, 0L, 75L, 75L, 0L, 50L, 25L), c(50L, 0L, 0L, 0L, 100L, 25L, 0L, 0L,

?s 18:35 de 27/03/2025, Daniel Lobo escreveu: > Hi, > > I have below minimization problem > > > MyDat = structure(list(c(50L, 0L, 0L, 50L, 75L, 100L, 50L, 0L, 50L, 0L, > 25L, 50L, 50L, 75L, 75L, 75L, 0L, 75L, 75L, 75L, 0L, 25L, 75L, > 75L, 0L, 75L, 100L, 0L, 25L, 100L), c(75L, 0L, 0L, 50L, 100L, > 50L, 75L, 75L, 100L, 25L, 0L, 25L, 100L, 0L, 50L, 0L, 25L, 25L, >

======= 2005-12-06 22:16:17 伳侜佋佢伬伌佇伵佒佇佇伌伒伬仯伜======= >Martin Maechler a 侀crit : > >> please, please, these trailing ";" are *so* ugly. >> This is GNU S, not C (or matlab) ! >> >> but I'll be happy already if you could >> drop these ugly empty statements at the end of your lines... > >May I disagree ? >I find missing ";" at

I used to consider using R and "Optim" to replace my commercial packages: Gauss and Matlab. But it turns out that "Optim" does not converge completely. The same data for Gauss and Matlab are converged very well. I see that there are too many packages based on "optim" and really doubt if they can be trusted! -- View this message in context:

I try to code the ULS factor analysis descrbied in ftp://ftp.spss.com/pub/spss/statistics/spss/algorithms/ factor.pdf # see PP5-6 factanal.fit.uls <- function(cmat, factors, start=NULL, lower = 0.005, control = NULL, ...) { FAfn <- function(Psi, S, q) { Sstar <- S - diag(Psi) E <- eigen(Sstar, symmetric = TRUE, only.values = TRUE) e <- E$values[-(1:q)] e <-

Hi! I'm translating some code from Matlab to R and I found a problem. I need to translate Matlab's function 'lsqnonlin' (http://www-ccs.ucsd.edu/matlab/toolbox/optim/lsqnonlin.html) into R, and at the beginning I thought it would be the same as R's 'optim'. But then I looked at the definition of 'lsqnonlin' and I don't quite see how to make

Hi, I'm having a problem converting a Matlab program into R. The R code works almost all the time, but about 4% of the time R's optim function gets stuck on a local minimum whereas matlab's fminsearch function does not (or at least fminsearch finds a better minimum than optim). My understanding is that both functions default to Nelder-Mead optimization, but what's different about