similar to: forecast using arfima

>>>>> 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

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

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

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

Hello. I'm trying to make k-step-ahead forecasts using ARFIMA(0, d, 0) models by taking the first T+k-1 coefficients in the binomial expansion of (1-B)^d, regarding (1-B)^d x(T+k) as an AR(T+k-1) on x(T+k), where x(T) is the series value at time T and k = 1, 2, 3, . That is, I forecast the series k values forward using the first T+k-1 coefficients in the binomial expansion of (1-B)^d as

please help.. I have estimate the value of parameter for AR,MA and fractional d.but I have problem on having the right command for forecasting ARFIMA model.please help...... -- View this message in context: http://r.789695.n4.nabble.com/how-to-make-ARFIMA-forecast-by-using-r-tp3869928p3869928.html Sent from the R help mailing list archive at Nabble.com.

Hi all, First: I have a small line of code I'm applying to a variable which will be placed in a matrix table for latex output of accuracy measures: acc.aarima <- signif(accuracy(forecast(auto.arima(tix_ts, stepwise=FALSE), h=365)), digits=3). The time series referred to is univariate (daily counts from 12-10-2010 until 5-8-2010 (so not 2 full periods of data)), and I'm working on

I would like to compute the next 15 observations for an ARFIMA(2,1,0) model along with confidence intervals. Can someone provide code? Many thanks. Jill ____________________________________________________________________________________ [[elided Yahoo spam]]

Please I want to perform full data analysis using ARFIMA model but I dont know the right package that can perform all the necessary test on the time series data. ERIC AIDOO [[alternative HTML version deleted]]

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

Hi, I would like to create variables in R containing parameters of summary(*Forecast Results*). Using the following code: library(forecast) data <- AirPassengers xets <- ets(data, model="ZZZ", damped=NULL) xfor <- forecast(xets,h=12, level=c(80,95)) summary(xfor) the output is: Forecast method: ETS(M,A,M) Model Information: ETS(M,A,M) Call: ets(y = data, model =

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,

I've some demand data, for which I wish to judge what will be the direction in the forecast period (Up/Down). What will be a best ML method to do this? Currently I'm using the data given below - 9/4/2016 241 9/11/2016 233 9/18/2016 226 9/25/2016 282 10/2/2016 291 10/9/2016 282 10/16/2016 308 10/23/2016 291 10/30/2016 268 11/6/2016 262 11/13/2016 273 11/20/2016 262 11/27/2016 309 12/4/2016

Hello all, This is a request for help from somebody who has the Ox interfaces working in R. I am trying to get the Ox interfaces working for Arfima and Garch modelling. However, I am having several problems: 1. The link to download G at rch_v40 does not work. Does anybody have a copy to email to me please? 2. Various guides offer different instructions for installing Ox in the correct place

Dear R users, I'm trying to use the "strucchange" package to determine structural breaks in an ARFIMA model. Unfortunately I'm not so familiar with this topic (and worse, I'm a beginner in R), so I don't know exactly how to specify my model so that the "Fstats","sctest" and "breakpoint" functions to recognize it and to calculate the

Hola, ¿hay alguna librería que sirva para modelizar la inflación utilizando un modelo modelo fraccionalmente integrados ARFIMA-STVGARCH? Saludos, Sebastián.

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