similar to: ARIMA, xreg and intercepts

Hi, I have been using this website ( http://www.stat.pitt.edu/stoffer/tsa2/Rissues.htm http://www.stat.pitt.edu/stoffer/tsa2/Rissues.htm ) to help me to fit ARIMA models to my data. At the moment I have two possible methods to use. Method 1 If I use arima(ts.data, order=c(1,2,0), xreg=1:length(ts.data)) then the wrong value for the intercept/mean is given (checked on SPSS and Minitab) and

Hi all, I have two time series that I would like to correlate but as they are autocorrelated, I am "pre-whitening" them first by fitting ARIMA models, then correlating their residuals....as described in https://onlinecourses.science.psu.edu/stat510/?q=node/75 However, http://www.stat.pitt.edu/stoffer/tsa2/Rissues.htm discusses some issues with ARIMA in R. In particular, for issue 2, if

I have written before, but to no avail. I have found two minor problems with fitting time series models with R. The thing is, they may be solved with MINOR adjustments to the code. I have posted these problems with detailed examples here: http://www.stat.pitt.edu/stoffer/tsa2/Rissues.htm Briefly, the problems are (1) When fitting time series models when there is an AR term present, the

Hi, I have been using this site ( http://www.stat.pitt.edu/stoffer/tsa2/Rissues.htm) to help me with some ARIMA modelling in R. Unfortunately the methods mentioned do not appear to work with second order differencing; arima(*, 2, *). I have used some dummy data to illustrate my point. When I use the xreg=... method, the estimate of intercept is *way* off. This can be seen by the high s.e but I

Hello all, I''m having fun again with the arima function. This time I read in: http://www.stat.pitt.edu/stoffer/tsa2/R_time_series_quick_fix.htm <<It has recently been suggested (by a reliable source) that using xreg in arima() does NOT fit an ARMAX model [insert slap head icon here]. This will be investigated as soon as time permits.>> (by R.H. Shumway & D.S. Stoffer)

Hi, My query is related to ARIMA function in stats package. While looking for the time series literature I found following link which highlights discrepancy in "arima" function while dealing with differenced time series. Is there a substitute function similar to "sarima" mentioned in the following website implemened in R? Any pointers would be of great help.

Dear R, I have find a website where they report problem with ARIMA models in R. I run the examples there and they give result as shown on the website. Does this mean that nothing has corrected in R? Maybe you not have seen the page, but the author said he contacted you. Here is the URL: http://www.stat.pitt.edu/stoffer/tsa2/Rissues.htm I like to know your opinion. Mvh. Marie [[alternative

Dear R, I have find a website where they report problem with ARIMA models in R. I run the examples there and they give result as shown on the website. Does this mean that nothing has corrected in R? Maybe you not have seen the page, but the author said he contacted you. Here is the URL: http://www.stat.pitt.edu/stoffer/tsa2/Rissues.htm I like to know your opinion. Mvh. Marie [[alternative

Hi, I am trying to understand exactly what xreg does in arima. The documentation for xreg says:"xreg Optionally, a vector or matrix of external regressors, which must have the same number of rows as x." What does this mean with regard to the action of xreg in arima? Apparently somehow xreg made the following two arima fit equivalent in R: arima(x, order=c(1,1,1), xreg=1:length(x)) is

Dear R-help-archive.. I am trying to figure out how to make arima prediction when I have a process involving multivariate time series input, and one output time series (output is to be predicted) .. (thus strictly speaking its an ARMAX process). I know that the arima function of R was not designed to handle multivariate analysis (there is dse but it doesnt handle arma multivariate analysis, only

I am having some issues with differencing using auto.arima when also specifying an xreg dataframe. The xreg dataframe contains dummy variables that specify time periods that had a promotion running. When I model diff(y) with order (1,0,1), the coefficients for these dummy variables are very different than when I model y with order=(1,1,1). I think when modeling diff(y) the coefficients

I am trying to understand how to fit an ARMAX model with the arima function from the stats package. I tried the simple data below, where the time series (vector x) is generated by filtering a step function (vector u, the exogenous signal) through a lowpass filter with AR coefficient equal to 0.8. The input gain is 0.3 and there is a 0.01 normal white noise added to the output: x <- u

When I run predict.Arima in my code, I get warnings like: Warning message: In cbind(intercept = rep(1, n), xreg) : number of rows of result is not a multiple of vector length (arg 1) I think this is because I'm not running predict.Arima in the same environment that I did the fit, so the data object used in the fit is no longer present. Looking at the predict.Arima source,

Hello all, I use arima to fit the model with fit <- arima(y, order = c(1,0,1), xreg = list.indep, include.mean = TRUE) and would like to use predict() to forecast: chn.forecast <- rep(0,times=num.record) chn.forecast[1] <- y[1] for (j in 2:num.record){ indep <- c(aa=chn.forecast[j-1], list.indep[j,2:num.indep]) # this is the newxreg in the

hi: you should probably send below to R-Sig-Finance because there are some econometrics people over there who could also possibly give you a good answer and may not see this email ? Also, there's package called mar ( I think that's the name ) that may do what you want ? Finally, I don't know how to do it but I think there are ways of converting a multivariate arima into the

I am using arima to develop a time series regression model, I am using arima b/c I have autocorrelated errors. Several of my independent variables are categorical and I have coded them as factors . When I run ARIMA I don't get any warning or error message, but I do not seem to get estimates for all the levels of the factor. Can/how does ARIMA handle factors in xreg? here is some example

Hello, Does anyone know how the parameter estimates are calculated for xreg variables when called as part of an arima() command, or know of any literature that provides this info? In particular, I was wondering if there is a quick way to compare different combinations of "xreg" variables in the arima() fit in the same way that you would in multiple regression (using AIC & R^2

Hello everybody! I have a problem when I try to perform a forecast of an ARIMA model produced by an auto.arima function. Here is what I'm doing: c<-auto.arima(fil[[1]],start.p=0,start.q=0,start.P=0,start.Q=0,stepwise=TRUE,stationary=FALSE,trace=TRUE) # fil[[1]] is time series of monthly data ARIMA(0,0,0)(0,1,0)[12] with drift : 1725.272 ARIMA(0,0,0)(0,1,0)[12] with drift

Dear all, When I run an arima(1,1,1) on an I(1) variable, y, I get different estimates to when I first difference the variable myself, e.g y2<-diff(y), and then run arima(1,0,1) on y2. Shouldn't these two approaches give the same output? Any help will be much appreciated. george

Hi everyone, I'm trying to include an external regressor in my ARIMA model but am having some problems with the data format in R. I've named my dependent variable of interest "count" and the external regressor "abc". The external regressor is a binary variable. Here are the contents of "abc" and the model I've attemped (along with its error message):