similar to: Defining time series objects

Has arima.mle (MASS, Ch.15, p.464) been implemented in R? [A search through contributed packages and R-FAQ suggests not, and I don't think function 'lme' from package 'nlme' would accomplish the same sort of thing, although it permits correlated errors. A search of the CRAN site shows this question has been asked some time ago, and it was suggested that Paul Gilbert's

I did a regression with ARMA errors using arima0 with ari<-arima0(y,order=c(2,0,2),xreg=reg1,delta=-1) or ari<-arima0(y,order=c(2,0,2),xreg=reg1) where reg1 is the matrix of the regressors and when I see diag(ari$var.coef) I get negative terms. Do you know what this mean ? I try to change transform.pars to 0 or 1 but this crash R on Windows. Is it possible to test the significativity

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

I have a multivariate time series and I would like to build a forecasting model with both AR and MA terms, I think that this is possible in R. I have looked at the vars package and it looks like it is possible to estimate MA terms using the Phi and Psi functions but I am not sure how to incorporate the estimated terms into a forecasting model. I have also looked at the dse package, but have not

Hi there, just a short question : Is it possible to do a forecast for a sesonal time sereies (e.g. with Box Jenkins method) with R ?? ..sorry but I didn 't get it in the man-pages. thanx Chris -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or

Hi, I use R to do some ARIMA forecasting and R runs out of memory. The problem is that I have 20160 samples(which are quite alot) and when I try to fit the model it runs out of memory. I tried with memory.size() to change the limit, but it wouldn't work. Is there anything you can suggest? Is it possible R can use virtual memory? Thank you, Kosta

Hello everybody, I am writing a review paper about State Space models in R, and I would like to cover as many packages as I reasonably can. So far I am familiar with the following tools to deal with SS models: * StructTS, Kalman* (in stats) * packages dse[1-2] * package sspir * package dlm I would like to have some input from users who work with SS models: are there any other packages for SS

Hi, I am trying to forecast a model using predict.Arima I found arima model for a data set: x={x1,x2,x3,...,x(t)} arima_model = arima(x,order=c(1,0,1)) I am forecasting the next N lags using predict: arima_pred = predict(arima_model,n.ahead = N, se.fit=T) If I have one more point in my series, let's say x(t+1). I do not want to recalibrate themodel, I just want to forecast the next N-1

Here is my problem: Autoregressive models are very interesting in forecasting consumptions (eg water, gas etc). Generally time series of this type have a long history with relatively simple patterns and can be useful to add external regressors for calendar events (holydays, vacations etc). arima() is a very powerful function but kalman filter is very slow (and I foun difficulties of estimation)

Dear all, this may be a stupid question but... The underlying model in procedure arima0 is X[t] = a[1]X[t-1] + ... + a[p]X[t-p] + e[t] + b[1]e[t-1] + ... +b[q]e[t-q] Is it possible to get an estimate of e for every point t, t-1 etc. or at least an estimate of the variance of e? Thanks a lot in advance for any hints Kai Arzheimer

What is the difference between arima and arima0?

Hi all, Forecasting from an arima model is easy with predict. But I can't manage to backcast : invent data from the model before the begining of the sample. The theory is easy : take your parameters, reverse your data, forecast, and then reverse the forecast I've tried to adapt the predict function to do that (i'm not sure that the statistical procedure is fine (with the residuals),

Hello My name is greigiano am student of Applied Economics, Department of Rural Economy. I am working on an article forecasting, which use the dynamic linear model, a model state space. I am wondering all the commands in R, to represent the linear dynamic model and Kalman filter. I am available for any questions. -- DEUS Seja Louvado Que ELE Ilumine sua vida Assim como ELE tem Iluminado a Minha

Hello again, A different but related question to my last one: Does anyone know if one can easily estimate state-space models using ML and the kalman filter using R? I would be especially interested in a relatively flexible function that would allow for estimation of hyperparameters, or could be made to do so. Thanks Michael J. Roberts Resource Economics Division, PMT USDA-ERS 202-654-5557

Hi, I'm trying to go through the examples for function arima0() in ts package, i.e, >data(lh) >arima0(lh, order = c(1,0,0)) each time the call to arima0() causes a segmentation fault. I checked the earlier version (1.1.1) of R, the function arima0 works fine. Tracing the call indicates that the function "setup_starma" (in pacf.c under ts) interprets the addresses of the

Hi there, Does anyone know how to predict ARMA? It doesn?t have either predict or forecast methods. I found couple of packages called fbasic and fseries at http://www.itp.phys.ethz.ch/econophysics/R/, which has ?arma.predict? in it, but it doesn?t seem to be working. Any help in this regard would be appreciated. Thanks in advance. Regards Skanda Kallur "Prediction is very difficult,

Dear R People: I'm trying to use the predict command on an arima0 object. I do the following: xm.arma <- arima0(xm2,order=c(1,0,1)) predict(xm.arma,n.ahead=2) and I get the message: Error in round(x, digits) : Non-numeric argument to mathematical function Any ideas what the problem might be, please? R version 1 4 1 on Windows. Thanks in advance! Sincerely, Erin Hodgess Associate

Full_Name: Ahmad Abu Hammour Version: rw0651 OS: windows 95 Submission from: (NULL) (63.23.128.44) Although I know that "ts package" is preliminary, I wanted to compare the results from R and SPSS. I ran ARIMA(2,1,2) in both softwares. I got NaN in standard errors of coefficients from R and real figures from SPSS. I changed "delta" in R to match that used by SPSS, I received

Hello, Using the dse package I have estimated a VAR model using estVARXls(). I can perform forecasts using forecast() with no problems, but when I try to use simulate() with the same model, I get the following error: Error in diag(Cov, p) : 'nrow' or 'ncol' cannot be specified when 'x' is a matrix Can anyone shed some light on the meaning of this error? How can I

[accidentally sent to owner-r-help -- please do NOT! it's "r-help" !] ------- start of forwarded message ------- From: Marcos_Sanches at gallup.com To: owner-r-help at stat.math.ethz.ch Subject: How to get residuasl with arima0? Date: Wed, 19 Sep 2001 15:19:07 -0300 I know this is a basic question, but I've never used the 'ts' package and I'm having some