similar to: Bug report for fracdiff

>>>>> akshay kulkarni >>>>> on Wed, 31 May 2023 20:55:33 +0000 writes: > dear members, > I am using arfima() from forecast package to model a time > series. The following is the code: >> LYGH[[202]] > [1] 45.40 3.25 6.50 2.15 >> arfima(LYGH[[202]]) > Error in .fdcov(x, fdf$d, h, nar = nar, nma = nma,

dear members, I am using arfima() from forecast package to model a time series. The following is the code: > LYGH[[202]] [1] 45.40 3.25 6.50 2.15 > arfima(LYGH[[202]]) Error in .fdcov(x, fdf$d, h, nar = nar, nma = nma, hess = hess, fdf.work = fdf$w) : NA/NaN/Inf in foreign function call (arg 5) I tried viewing .fdcov() with the following code:

Dear Martin, Sad that the bug is beyond your ken... Fortunately, the error happens only rarely...The length of LYGH was 719 and there were only two such errors..I will just replace them with NA and make do. By the by, what if I send LYGH as an attachment to your actual mail ( not the r-help mail)? Will it help? Can you then pinpoint the cause? Or should I raise a bug

Dear list and Martin, I'm testing different approaches to fit an electricity demand time series and come upon the fracdiff package (v 1.3-1) for fitting fractional ARIMA models. The following questions are motivated by this package. 1. Despite having a help page, the residuals and fitted functions don't seem to have implementation, or did i miss something obvious? Alternatively, having a

Hi,I have a question about the fracdiff.var function (package fracdiff) which goal is to recompute more precise confidence intervals for the parameters estimated by fracdiff (or arfima). More precisely, it deals with the standard error of the "d" coefficient : Is it normal that the standard error of the "d" coefficient can be brought customly close to zero by decreasing the

I've put all ``current'' add-on packages into CRAN's source/contrib tree and created an INDEX file (attached below). As you can see, currently we have acepack bootstrap ctest date e1071 fracdiff gee jpn snns splines survival4 (Yes, e1071 and jpn are new ... more on the latter in a later mail.) In the near future, I am hoping for the following: oz (Bill

Hi I'm using fracdiff package to estimate the parameters of a fractionally-differenced ARIMA (p,d,q) model, and it works fine, but I wanted to have also the filtered series and the series of residuals. I understand these are calculated in the subroutine fdfilt, in the program fdcore.f, but I can't manage to get them out. Any suggestion would be much appreciated Thanks Susana Barbosa

Full_Name: Jussi Mäkinen Version: 1.6.2 OS: Win2000 Submission from: (NULL) (193.210.145.2) I tried to download fracdiff from http://www.stat.unipg.it/stat/statlib/R/CRAN/ but I got the messages box: The procedure entry point daxpy_ could not be located in the dynamic link library R.dll and the following lines to RGui: Error in dyn.load(x, as.logical(local), as.logical(now)) : unable

Hello! I used the function fracdiff(dn, nar=1, nma=1) and got the values of d, ar and ma coefficients. Also another coefficients were get under fdGPH, fdSperio. How could I get the forecasts in these models? Thank you very much [[alternative HTML version deleted]]

Hi, I'm using the function fracdiff and can not figure out how to get the estimated values for sigma2 or confidence intervals for the parameter estimates. Does anyone know how to obtain these values? Thanks, Melissa

Hi, I am using the fracdiff package to estimate the parameters of an ARFIMA(1,d,1) model. I would also like to get the residuals of the series. I have seen another post about this (below). However, being still quite at the beginner level in terms of R, I did not quite understand how this worked. I also read through the fracdiff package manual with no success to find any help with the

Does anybody know if it is possible to forcast or predict from a fracdiff object? Any help would be much obliged... Cheers, Alan

Dear folk, I am stempting to estimate a vector error correction model using a seemingly fractionally integrated multivariate time series. The *fracdiff *package provides tools to estimate degree of fractional integration. But *fracdiff *can't help me to: 1. test equality of two degrees of fractional integration, say d1=d2? 2. estimate a multivariate cointegrating error correction model,

Dear all, I want to assess the question whether several time series of parties' respective popularities are fractionally integrated. The "fracdiff" package seems to be an obvious choice. What confuses me is that the 'd' parameter estimated by fracfiff seems to be bound to a range from 0 to 0.5. From what I have read I would assume it should be allowed to vary between 0 and

jussi.makinen@valtiokonttori.fi wrote: > Full_Name: Jussi M?kinen > Version: 1.6.2 > OS: Win2000 > Submission from: (NULL) (193.210.145.2) > > > I tried to download fracdiff from http://www.stat.unipg.it/stat/statlib/R/CRAN/ > but I got the messages box: That's not a current mirror of CRAN (see the CRAN Master for recent mirrors), it's last update seems to be

Hello. I want to specify a diagonal structure for the covariance matrix of random effects in the lme() function. Here is the call before I specify a diagonal structure: > fit2<-lme(Ln.rgr~I(Ln.nar-log(0.0011)),data=meta.analysis, + random=~1+I(Ln.nar-log(0.0011)|STUDY.CODE,na.action=na.omit) and this works fine. Now, I want to fix the covariance between the between-groups slopes

Robust Covariance Estimation Software via Nearest Neighbor Variance Estimation (NNVE) Software to carry out robust covariance estimation by Nearest Neighbor Variance Estimation (NNVE) [Wang and Raftery (2002, J. Amer. Statist. Ass.)] is now available for R and Splus. In the simulation studies published in JASA, this had mean squared error at least 100 times smaller than that of other leading

Robust Covariance Estimation Software via Nearest Neighbor Variance Estimation (NNVE) Software to carry out robust covariance estimation by Nearest Neighbor Variance Estimation (NNVE) [Wang and Raftery (2002, J. Amer. Statist. Ass.)] is now available for R and Splus. In the simulation studies published in JASA, this had mean squared error at least 100 times smaller than that of other leading

I'd like to play with ARIMA models of stock prices, but I am a complete novice. Could some kind soul explain the relationship among packages "ts", "tseries", "dse", "dse2", and "fracdiff"? Are they 'competing' products or does one depend on another? Where would be the best place for a novice to begin? Thanks for any advice. PS. I

Hi! The nobs() method for glm objects always returns the number of cases with non-null weights in the data, which does not correspond to the number of observations for Poisson regression/log-linear models, i.e. when family="poisson" or family="quasipoisson". This sounds dangerous since nobs() is, as the documentation states, primarily aimed at computing the Bayesian