similar to: can't install rugarch and nloptr packages in R 3.01 opensuse linux

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.

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, i am unable to install the rugarch package. More than that i do not even find this package in my list of possible packages. Its possible than the name has changed, or the package is not longer availiable? Is there a similar package avaliable for garch modelling except the fGarch what i am using now? many Thanks Roland -- View this message in context:

Hi, I`m about to switch from STATA to R and have serious troubles to find proper documentations on the internet. Right now I try to find a proper documentation of the eGARCH model being part of the rugarch package. Neither here http://cran.r-project.org/web/packages/rugarch/vignettes/Introduction_to_the_rugarch_package.pdf nor here http://cran.r-project.org/web/packages/rugarch/rugarch.pdf could

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):

Hi I was trying to implement Egarch (1,1) with Student t distribution using rugarch. But I was not getting any value. Following were the commands that I was using: library(rugarch) spec=ugarchspec(variance.model=list(model="eGARCH", garchOrder=c(1,1)), mean.model=list(armaOrder=c(1,1), arfima=FALSE), distribution.model="std") fit=ugarchfit(data=b,spec=spec) sigma(fit) May I

On Thu, May 3, 2018 at 2:03 PM, Michael Ashton <m.ashton at enduringinvestments.com> wrote: > 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. :-) > I'm very confused by these statements. Most of the "finance tools"

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 Michael, A few comments 1. To add the constraint sum(wgt.vect=1) you would use the method of Lagrange multipliers. What this means is that in addition to the w_i (the components of the weight variables) you would add an additional variable, call it lambda. Then you would modify your optim.fun() function to add the term lambda * (sum(wgt.vect - 1) 2. Are you sure that you have defined

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

Let me start with the code: library(quantmod) library(rugarch) getSymbols("SPY", from="1900-01-01") rets=na.trim(diff(log(Cl(SPY)))) tt = tail(rets["/2004-10-29"], 1000) spec = ugarchspec(variance.model=list(garchOrder=c(1,1)), mean.model=list(armaOrder=c(2,5)), distribution.model="sged") for(ii in 1:10) { ttFit = ugarchfit( spec=spec,

Dear all, I want to backtest my Value at Risk output using the VaRTest() function in the rugarch package. I do not understand if the numeric vector of VaR which needs to be calculated is in negative or positive terms. Usually VaR is expressed in positive terms. Do I have to use positive values for VaR in the VaRTest() formula? Thanks for your help. [[alternative HTML version deleted]]

Hi guys, does anyone know if there is the possibility to fit a gamma distribution using ugarch?honestly i don't know if maybe is possible to fix some parameters that reduce ghyp or ged in a gamma distribution.. thanks a lot sara -- View this message in context: http://r.789695.n4.nabble.com/gamma-distribution-in-rugarch-package-tp4637893.html Sent from the R help mailing list archive at

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

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 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') #

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

My code: spec<-ugarchspec(variance.model = list(model = "sGARCH", garchOrder = c(1, 1), submodel = "Null", external.regressors = NULL, variance.targeting = FALSE), mean.model = list(armaOrder=c(0,0),include.mean =FALSE, archm = FALSE, archpow = 1, arfima = FALSE, external.regressors = NULL, archex = FALSE), distribution.model = "norm", start.pars = list(),