similar to: Memory problems

What is the difference between arima and arima0?

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)

I have a data file with a given time series of price data and I would like to split the time series into a test set and training set. I would then like to build an ARIMA model on the training set and apply this model on test set. Below is some code: [CODE] data= read.table("A.txt",sep=",") attach(data) training = data[1:120, 6] test = data[121:245, 6] ts1 = ts(training) ts2 =

Thanks, Can't find an ARIMA in base, dse1/2 or tseries, only references to. What package is it in? Thanks again! Best regards, /fb -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the

HI, there, When i use R, i tried to use function arima(), it complains: Error: couldn't find function "arima" But when I type "help.search("arima") ", I got arima() poped up.. arima(ts) ARIMA Modelling of Time Series arima.sim(ts) Simulate from an ARIMA Model arima0(ts) ARIMA Modelling of Time Series -- Preliminary

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),

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

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

Hi, I've noted that not all `predict' methods are hidden in the namespace: > methods("predict") [1] predict.ar* predict.Arima* [3] predict.arima0* predict.glm [5] predict.HoltWinters* predict.lm [7] predict.loess* predict.mlm [9] predict.nls* predict.poly [11] predict.ppr* predict.prcomp* [13]

Hello, I would like to study time series with ARIMA and GARCH models. I installed R-Plus and its libraries but when I try to execute the function arima0, It answers that the function does not exist. Could you help me or give me references of papers dealing with arima and garch in R-Plus? Thanks Beno?t, ___________________________________ Mr. Beno?t LACHERON Rue de l'industrie, 44, 1040

Dear R users, I would like to simulate, for 20000 replications, an autoregressive process: y(t)=0.8*y(t-1)+e(t) where e(t) is i.i.d.(0,sigma*sigma), Thank you in advance ____________________________________________________ Écoutez gratuitement le nouveau single de Noir Désir et découvrez d'autres titres en affinité avec vos goûts musicaux

I'm using the fixed argument in arima. Shouldn't ar4, ar5, and ar6 display as zero in the output? Call: arima(x = window(log(hhprice), start = c(1990, 1), end = c(2003, 3)), order = c(7, 1, 0), xreg = window(ts.union(exa1 = lag(exa, -1), exa12 = lag(exa, -12), exb1 = lag(exb, -1), exc1 = lag(exc, -1), exc12 = lag(exc, -12)), start = c(1990, 1), end = c(2003, 3)),

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,

Hi, In my ongoing quest to track down the source of an error (see message "[R] optim error in arima" above), I find in the cource code for arima0 the following: arma0f <- function(p) { par <- as.double(fixed) par[mask] <- p .Call("arma0fa", G, par, PACKAGE = "stats") } I would like to know what the function

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

Dear All, R 1.9.1, Windows When copying and pasting a few lines from the 'predict.Arima' help, I get an error message: > data(lh) > predict(arima(lh, order = c(3,0,0)), n.ahead = 12) Error in eval(expr, envir, enclos) : Object "xreg" not found On the other hand, the following is OK: > data(lh) > predict(arima0(lh, order = c(3,0,0)), n.ahead = 12) $pred Time

Hi, I am trying to estimate an ARIMA model in the case where I have some specific knowledge about the coefficients that should be included in the model. Take a classical ARIMA (or even ARMA) model: P(B) X(t) = Q(B) epsilon(t), where X(t) is the data, epsilon is a white noise, B is the backward operator and P and Q are some polynoms. Additionally, assume that you know in advance how P and Q

Hi, I have a suggestion for the fonction arima and arima0. I think you should not call the constant an intercept because it creates confusion. It is not really an intercept but a mean. For an AR(1) the intercept mu should be defined as: X(t)=mu + phi X(t-1) + e(t) What you call intercept mu is rather defined as (X(t)-mu) = phi (X(t-1)-mu)) + e(t) which is not a common way to define an

Hi again With arima0 the problem was solved but what are the diferences between arima and arima0? I have another question. I fit the model to the data and I make some predictions. But I also want to calculate MAPE based in the last 3 observations available. Is it possible? Can I obtain the fitted values from the model? thanks~ luis -- SAPO ADSL.PT, apanhe j? o comboio da Banda Larga. Kit