similar to: R 1.7.1 arima0 problem

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

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

Dear all R users, Suppose, Dear all R users, Suppose, pauto.cor = pacf(lh, plot=F) max.lag = max(pauto.cor$lag) min.lag = min(pauto.cor$lag) centre = (max.lag - min.lag)/2 pauto.cor = pauto.cor$acf pauto.cor = pauto.cor[-1] par(mar=c(3,0,1,1)) barplot(pauto.cor, axes=F,xlim=c(max(pauto.cor), min(pauto.cor)), space=0, col="green4",border="green",horiz=T) #This plots

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

two ARIMA models, both have several bars signicant in ACF and PACF plots of their residuals, but when run Ljung Box tests, both don't show any significant correlations... however, one model has p-value that is larger than the other model, based on the p-values, can I say the model with larger p-values should be better than the model with smaller p-values? [[alternative HTML version

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

What is the difference between arima and arima0?

[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

When I use the command for PACF, lags 5, 10, 15, and 20 are labeled. I would like to label lag 1. I would greatly appreciate if someone could tell me how to do this. Below is the command that I am using: pacf(data$R1,main="Series R1 Residuals") [[alternative HTML version deleted]]

Full_Name: Arto Luoma Version: 1.1.0 OS: Windows 98 Submission from: (NULL) (153.1.53.119) In arima0 it is possible to specify whether the mean of the original series is included in the model or not. However, it is not possible to specify whether the mean of the differenced series is included. It seems that it is not included. However, if differencing is used to eliminate trend, the mean of the

Dear R People: Suppose I want to estimate the parameters of the following AR model: (1 - phi_1 B - phi_2 B^2 - phi_9 B^9) x_t = a_t and I want to use the arima0 command from the ts library. How would I use the order subcommand, please? R Version 1.4.1 for Windows. Thanks! Sincerely, Erin Hodgess Associate Professor Department of Computer and Mathematical Sciences University of Houston -

Dear R Developers: Is there a way to look at the underlying code from such items as R_setup_starma, please? Thanks, Erin Erin M. Hodgess, PhD Associate Professor Department of Computer and Mathematical Sciences University of Houston - Downtown mailto: hodgesse@uhd.edu [[alternative HTML version deleted]]

pacf in devel seems by default to return a different number of lags than 1.7.1 for $pacf. I don't see any mention of this in the NEWS file, or any change in the documentation, so I suspect it is and error, though it may be an undocumented improvement. (Newbie question: How is the simplest way to display a function like pacf.default that is not exported from a namespace?) Paul

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

Here is the summary on predict when using an arima0 object: The arima0 object must be based on a time series vector. That is; x <- ts(xm1, frequency=12, start=c(1975,1)) x.ar <- arima0(x,order=c(1,1,1)) predict(x.ar,n.ahead=3) Thanks so much to Prof. Brian Ripley and David Brahm and other! Sincerely, Erin Hodgess

hi, in 1.9.1, the return value from ARMAacf(pacf=TRUE) is not named by lags, contrary to ?ARMAacf. the simple fix is to move names(Acf) <- down after if(pacf), with an appropriate starting lag as pacf=TRUE appears to start at lag 1 (whereas pacf=FALSE starts at lag 0). for consistency, one could argue to append 1 for lag 0 for pacf=TRUE (or start pacf=F at lag 1). however, given the

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

How can I make sure the residual signal, after subtracting the trend extracted through some technique, is actually trend-free ? I would greatly appreciate any suggestion about some Stationarity tests. I'd like to make sure I have got the difference between ACF and PACF right. In the following I am citing some definitions. I would appreciate your thoughts. ACF(k) estimates the correlation

I am getting the following: *** Weave Errors *** Error in driver$runcode(drobj, chunk, chunkopts) : Error in eval(expr, envir, enclos) : couldn't find function "pacf.mts" *** Source Errors *** Error in eval(expr, envir, enclos) : couldn't find function "pacf.mts" make[1]: *** [checkVignettes] Error 1 I don't really understand the new namespace mechanism,

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