similar to: hessian matrix in arima

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

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

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:

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:

Hi there! I´m a noob when it comes to R and I´m using it to run statisc analysis. With the code for ARIMA below I´m getting this error: Error in solve.default(res$hessian * n.used) :Lapack routine dgesv: system is exactly singular The code is: > s.ts <- ts(x[,7], start = 2004, fre=12) > get.best.arima <- function (x.ts, maxord=c(1,1,1,1,1,1)) + { + best.aic <- 1e8 + n <-

Hello R experts! 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: Error en

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

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

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

Hi R-help! I'm trying to understand how R's nlm function updates its estimate of the Hessian matrix. The Dennis/Schnabel book cited in the references presents a number of different ways to do this, and seems to conclude that the positive-definite secant method (BFGS) works best in practice (p201). However, when I run my code through the optim function with the method as "BFGS",

Hi I am trying to recover the hessian of a problem optimised with box-constraints. The problem is that in some cases, my estimates are very close to the boundary, which will make optim(..., hessian=TRUE) or optimHessian() fail, as they do not follow the box-constraints, and hence estimate the function in the unfeasible parameter space. As a simple example (my problem is more complex though,

Hello all useRs, I am using the OPTIM function with particular interest in the method L-BFGS-B, because it is a box-constraint method. I have interest in the errors estimates too. I make: s.e. <- sqrt( diag( solve( optim(...,method='L-BFGS-B', hessian=TRUE)$hessian ))) but in help say: "Note that this is the Hessian of the unconstrained problem even if the box constraints

Hi I fitted an ARIMA model using the function arima(). The output consists of the fitted coefficients with their standard errors. However i need information about the significance of the coefficients, like p-values. I hope you can help me on that issue... ciao Stefan

R users; A question about optimization within R. I've been using both optim() and nlminb() to estimate parameters and all seems to be working fine. For context (but without getting into specifics - sorry), I'm working with a problem that is known to have correlated parameters, and parameter estimation can be difficult. I have a question on optim() - I'm using

Dear All, I am running a simulation to obtain coverage probability of Wald type confidence intervals for my parameter d in a function of two parameters (mu,d). I am optimizing it using "optim" method "L-BFGS-B" to obtain MLE. As, I want to invert the Hessian matrix to get Standard errors of the two parameter estimates. However, my Hessian matrix at times becomes

Hi, my name is Marcel R. Lopes. My problem is, I made a code to calculate the estimates of a Cox model with random effects. Used to optimize the R command for this. The estimates were calculated correctly, but the Hessian matrix does not have good values. The same thing was done in SAS and gave good results for the Hessian Matrix. Where is the problem in R? As the Hessian is calculated?. How

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:

Dear R Users Hi, I have very emergency problems in my programming about finding MLE with optim command. I reproduced it with real data. I guess that my function object in optim is very sensitive because it has power function . Then optim give me lower or initial values for estimates with these warnings for Hessian matrix computation: 1: In log(B2 * (C2^(y + v))) : NaNs produced 2: In log(B3