similar to: 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 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 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:

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

I was sniffing in the fracdiff library (this is for fractionally integrated ARMA processes; Haslett and Raftery 1989). The documentation suggests that one tries the following simple example: library(fracdiff) ts.test <- fracdiff.sim( 5000, ar = .2, ma = -.4, d = .3) fracdiff( ts.test$series, nar = length(ts.test$ar), nma = length(ts.test$ma)) When I run this, I get the following error: R

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

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

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

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

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

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

hi I'm puzzled as to the relation between the REML score computed by gam and the formula (4) on p.4 here: http://opus.bath.ac.uk/22707/1/Wood_JRSSB_2011_73_1_3.pdf I'm ok with this for poisson, or for quasipoisson when phi=1. However, when phi differs from 1, I'm stuck. #simulate some data library(mgcv) set.seed(1) x1<-runif(500) x2<-rnorm(500)

Hi, I believe I have significantly improved [dpq]wilcox functions by implementing Harding's algorithm: Harding, E.F. (1984): An Efficient, Minimal-storage Procedure for Calculating the Mann-Whitney U, Generalized U and Similar Distributions, App. Statist., 33, 1-6 Results on my computer show (against R-2.9.1): > system.time( dwilcox( 800, 800, 80) ) user system elapsed 0.240

Hello! I installed the fSeries package to get some farima time-series which i tried with farimaSim, but unfortunately i got always an error. I tried it this way: > farimaSim(n = 1000, model = list(ar = 0.5, d = 0.3, ma = 0.1), method="freq") Error in farimaSim(n = 1000, model = list(ar = 0.5, d = 0.3, ma = 0.1), : ... used in an incorrect context Some ideas? Regards, ___

Something that i would like to have, is the ability to keep the download packages in a temp directory when using febootstrap. I understand that using ferora/archlinux (distros with a lot of package updates every day) can increase the size of this temp directory rapidly and at some point will have a lot of deprecate packages. But the daily use of febootstrap (or building libguestfs) makes your

Hello List, first thanks for previous hints, you helped me a lot. Unfortunately i have new problem with sieve and executing multiple scripts sequentially. This is current conf which is complete working : #CONF1 plugin { sieve = ~/sieve/.dovecot.sieve sieve_plugins = sieve_extprograms sieve_extensions = +vnd.dovecot.pipe +vnd.dovecot.filter +vnd.dovecot.execute +editheader

I've discovered an infelicity (I guess) in qbeta(): it's not a bug, since there's a clear warning about lack of convergence of the numerical algorithm ("full precision may not have been achieved"). I can work around this, but I'm curious why it happens and whether there's a better workaround -- it doesn't seem to be in a particularly extreme corner of parameter

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

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,

Full_Name: M. Welinder Version: 1.8.1 OS: Solaris Submission from: (NULL) (65.213.85.227) Currently R has... #define R_D_Lval(p) (lower_tail ? (p) : (1 - (p))) /* p */ #define R_D_val(x) (log_p ? log(x) : (x)) /* x in pF(x,..) */ #define R_DT_val(x) R_D_val(R_D_Lval(x)) /* x in pF */ ...which is sub-optimal in the lower_tail==FALSE && log_p==TRUE case. Something like this ought