similar to: how to modify an R built-in function?

dhabby wrote: Last week I run in to a lot a problems triyng to fit an ARIMA model to a time series. The problem is that the internal process of the arima function call function "optim" to estimate the model parameters, so far so good... but my data presents a problem with the default method "BFGS" of the optim function, the output error looks like this:

Dear members of the list, I'm a beginner in R and I'm having some trouble with: "Error in optim(init[mask], armafn, method = "BFGS", hessian = TRUE, control = optim.control, : non-finite finite-difference value [8]" when running "arima". I've seen that some people have come accross the same problem:

Hi all, I?m using the arima() function to study a time series but it gives me the following error: Error en optim(init[mask], armafn, method = "BFGS", hessian = TRUE, control = optim.control, : non-finite finite-difference value [3] I know that I can change the method of the arima() to "CSS" instead of "ML" but I'm specially interested in using

Hi people, I´m trying to development a simple routine to run many Arima models result from some parâmeters combination. My data test have one year and daily level. A part of routine is: for ( d in 0:1 ) { for ( p in 0:3 ) { for ( q in 0:3 ) { for ( sd in 0:1 ) { for ( sp in 0:3 ) { for ( sq in 0:3 ) {

Hello, I'm fitting a series of ARIMA models to a data set to compare fits. After taking the logs of the data and then differencing them to induce stationarity, I execute arima( y, order=c( p, 0, q ), seasonal=list( order=c( P, 0, Q ), period=7 ) ) for various values of p, q, P and Q. For one set of these values, I get Error in optim(init[mask], armafn, method = "BFGS", hessian

Hi, recently I have started working with R (v. 2.7.2), and I have been using R's internal ARIMA_Like() function (from the "stats" package) to estimate some ARIMA models. In particular, I use ARIMA_Like() in a function "fn()" that I feed to the optim() method; the main goal is to find optimal ARIMA prediction models for some time series. The ARIMA_Like() function returns a

Rob J Hyndman gives great explanation here (https://robjhyndman.com/hyndsight/estimation/) for reasons why results from R's arima may differ from other softwares. @iacobus, to cite one, 'Major discrepancies between R and Stata for ARIMA' (https://stackoverflow.com/questions/22443395/major-discrepancies-between-r-and-stata-for-arima), assign the, sometimes, big diferences from R

In R devel rev.66393 (2014-08-15) it was possible to do this: trace(optim, exit = quote(str(returnValue()))) but returnValue() does not seem to be available any more. The above was useful to get the output of a function when it was called deep within another function that I have no control over. Has this been replaced by some other equivalent function? P.S. This demonstrates that it no

Dear Carlos and Kjetil, Thanks for your answer. >I do not think that is the way to go. If you believe that your algorithm >is better than the existing one, talk to the author of the package and >discuss the improvement. The whole community will benefit. I should be able to *easily* modify it and test it first! >Copy the existing function into a new file, edit it and load it via

Hello R experts! I'm running a FOR loop in which at every step an arima model is generated. The problem is some series produces numeric problems with optim. My question is if there is a way of telling to R that at every critical error of optim jumps to the next series instead of stopping the calculations. Or better yet, tell it to run another arima fit but with a different optmization

Thanks a lot to everybody that helped me out with this. Conclusions: (1) In order to edit arima in R: >fix(arima) or alternatively: >arima<-edit(arima) (2) This is not contained in the "Introduction to R" manual. (3) A "productive" fix of arima is attached (arma coefficients printed out and error catched so that it doesn't halt parent loops to search for

Hello everybody! I have an ARIMA model for a time series. This model was obtained through an auto.arima function. The resulting model is a ARIMA(2,1,4)(2,0,1)[12] with drift (my time series has monthly data). Then I perform a 12-step ahead forecast to the cited model... so far so good... but when I look the plot of my forecast I see that the result is really far from the behavior of my time

Dear members of the list, I''m a beginner in R and I''m having some trouble with: "Error in optim(init[mask], armafn, method = "BFGS", hessian = TRUE, control = optim.control, : non-finite finite-difference value [8]" when running "arima". I''ve seen that some people have come accross the same problem:

Hi, I am working or arima. I think arima uses non-linear optimisation for parameter optimisation. The standard error for parameters are computed from hessian matrix. When I use arima model, how can I see the finial hessian got from non-linear optimisation (BFGS for example). Any help is appreciated. Many thanks. Di [[alternative HTML version deleted]]

>If you ***look at the code*** for arima you will see that ``%+%'' is >defined >in terms of a call to ``.Call()'' which calls ``R_TSconv''. So >apparently >R_TSconv is a C or Fortran function or subroutine in a ``shared >object library'' >or dll upon which arima depends. Hence to do anything with it you'll >need to get >that shared

Having worked with optim() and related programs for years, it surprised me that I haven't noticed this before, but optim() is inconsistent in how it deals with bounds constraints specified at infinity. Here's an example: # optim-glitch-Ex.R x0<-c(1,2,3,4) fnt <- function(x, fscale=10){ yy <- length(x):1 val <- sum((yy*x)^2)*fscale } grt <- function(x, fscale=10){ nn

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

Hi, dear R users I am a newbie in R and I wantto use the method of meximum likelihood to fit a Weibull distribution to my survival data. I use "optim" as follows: optim(c(1, 0.25),weibull.like,mydata=mydata,method="L-BFGS-B",hessian = TRUE) My question is: how do I setup the constraints so that the two parametrs of Weibull to be pisotive? Or should I use other function

Dear kind R-experts. Does anybody have an experience to use optim function? If yes, what is the main difference between two method "BFGS" vs "L-BFGS-B"? I used "BFGS" method and got what I wanted. But when I used "L-BFGS-B" the error message said that "L-BFGS-B needs finite values of fn". So that means "BFGS" method can handle even if fn