similar to: arima/arima0 function

What is the difference between arima and arima0?

Could someone please give a brief explanation, or pointer to an explanation, of the following error: > arima(ts.growth, order = c(1,0,0),include.mean=T) Error in arima(ts.growth, order = c(1, 0, 0), include.mean = T) : non-stationary AR part from CSS and why it does not arise with > arima0(ts.growth, order = c(1,0,0)) Many thanks ____________________________ Dr. Daniel P. Bebber

Hi, I work on order estimation for autoregressive processes and after some inconsistencies cropped up I implemented the AIC criterion myself. Its results do not match the implementation in R and there are a few things I can not understand even after reading the source code of R. I used the function called arima0 (with empty "ma" coeficient vector), and I do not understand how some of

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, 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

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 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'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, the function makeARIMA(), designed to construct some state space representation of an ARIMA model, uses a C function called getQ0, which can be found at the end of arima.c in R source files (library stats). getQ0 takes two arguments, phi and theta, and returns the covariance matrix of the state prediction error at time zero. The reference for getQ0 (cited by help(arima)) is:

To whom it may concern: I am trying to better understand the functionality of 'R' when making arima predictions to avoid any "Black Box" disadvantages. I'm fitting a seasonal arima model using the following command (having already loaded 'stat' package). arimaSeason <- arima(Data,order=c(1,0,1),seasonal=list(order=c(1,0,1),period=12)) I can then generate

sseq <- c(1, seq(5, 120, by = 5)) for(i in 1:length(sseq)){ assign(paste("arima", i, sep=""), arima0(data.ts[sseq[i]:(sseq[i]+115)], order=c(1,1,1))) } pred1 = predict(arima1, n.ahead = 5, se.fit = TRUE)$pred how do I traverse the arima models so I repeat the above prediction procedure(bold) on all arima models. Also, how do i automatically create one huge vector of the

Looking at the arima.c code related to arima fitting I noticed that the code is mainly a merge of: - Gardner, G, Harvey, A. C. and Phillips, G. D. A. (1980) Algorithm AS154. An algorithm for exact maximum likelihood estimation of autoregressive-moving average models by means of Kalman filtering. Applied Statistics 29, 311–322. - Jones, R. H. (1980) Maximum likelihood fitting of ARMA models to

Hi I posted this problem yesterday but didn't get a reply so I try again today. I hope someone can help me with this. thank you very much for the help cheers Benedikt I would like to use arima () to find the best arima model for a time series. The default in arima apparently is to use conditional sum of squares to find the starting values and then use ML for the

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

> From: "Krassimir Krastev" <krastev at fas.harvard.edu> > To: "R-help" <r-help at stat.math.ethz.ch> > Date: Tue, 29 Feb 2000 11:56:49 -0500 > X-Priority: 3 (Normal) > X-MSMail-Priority: Normal > Importance: Normal > X-MimeOLE: Produced By Microsoft MimeOLE V5.00.2919.6600 > > Does anyone know of any comprehensive literature (like a

Thanks a lot to everybody that helped me out with this. Conclusions: (1) In order to edit arima in R: >fix(arima) or alternatively: >arima<-edit(arima) (2) This is not contained in the "Introduction to R" manual. (3) A "productive" fix of arima is attached (arma coefficients printed out and error catched so that it doesn't halt parent loops to search for

Hi, All, This is my program ts1.sim <- arima.sim(list(order = c(1,1,0), ar = c(0.7)), n = 200) ts2.sim <- arima.sim(list(order = c(1,1,0), ar = c(0.5)), n = 200) tdata<-ts(c(ts1.sim[-1],ts2.sim[-1])) tre<-c(rep(0,200),rep(1,200)) gender<-rbinom(400,1,.5) x<-matrix(0,2,400) x[1,]<-tre x[2,]<-gender fit <- arima(tdata, c(1, 1, 0), method = "CSS",xreg=t(x))

Hello, Does anybody know if the function arima with an external regressor (xreg) applies the auto correlation on the dependant variable or on the residuals. In comparison with SAS (proc autoreg), it seems that the auto correlation applies on the residuals but i'd like to have the confirmation. I want to estimate: Y[t] = a[1]*X[t] + a[2] + E[t] with E[t]=b[1]*E[t-1] Should I use : arima(Y,

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