similar to: Proper Usage of the XREG in ARIMA

Hi Folks, At the moment, I am at the stage where I can only do the back manual. I have run the first steps of configure and then make. Now when I run this command, I can be able to have files transfered to a remote server rsync -t (filename) (remote-location) forinstance rsync -t *.p dev:testing and doing this, I am still asked for the password for the remote server. I have tried copying

Greetings - I am hoping someone can confirm for me the steps that I am using to add an LV to an existing Guest in KVM, and what I am seeing as I do some of these steps. My host (earth) is CentOS 6 and so is my guest (disect). The guest (disect) is my testing server. The main objective of what I am trying to do is add a logical volume for /var into my guest. The LV (lv_disectvar) is part

Hi Folks, I am going through a hard time of finding a way of using rsync to make a remote backup (disaster recovery). I am trying to make use of rsync to have a backup outside our offices, incase of any disaster forinstance fire, we can be in position to recover our data. This is actually my first time using rsync and I have done the configure and make. I got stuck at the stage of creating a

I''ve got qualcomm''s qpopper2.2, and am not sure if its vulnerable. The advisory mentions pop and imap servers, but only says: version of IMAP (Section B). If your POP server is based on the University of Washington IMAP server code, you should also upgrade to the latest version of IMAP. Until you can take one of these actions, I installed the new imapd about 3

I've been studying some of the code and I'm still a little shakey on the proper method for returning a data.frame from a C function (which is my ultimate goal here). I've started some code that I've "stolen" from the archives and I'm running into crashes, etc. I've been trying to gleen some insight from the src/main/scan.c file and didn't find many comments in

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

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):

Hello everyone, Hope you all are doing great! I have been fitting arima models and performing forecasts pretty straightforwardly in R. However, I wanted to add a couple of regressors to the arima model to see if it could improve the accuracy of the forecasts but have had a hard time trying to do so. I used the following R function: arima(x, order = c(0, 0, 0), seasonal = list(order = c(0, 0,

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, I am fairly new to time series analysis, and I am wondering if anyone could point me to some good references related to mechanics of what is going on when you fit a model using arima that includes a set of external regressors (i.e., use the xreg= feature). Thank you, Spencer [[alternative HTML version deleted]]

Dear all, I am fitting an arimax (arima with some extra explanatory variables) model to a time series. Say, I have a Y (dependent variable) and an X (explanatory). Y is 100 observations (time series) and X is 100 + 20 (20 to use for the forecast horizon). I can not make xreg work with the forecast function for an arima fit. The "predict" function seems to be working but the

Hello. I've got a problem with arma/xreg. I would like to get a better model-fit by implenting some external explanatory variable, so I thought I can implement it by expand the arima-function with an xreg-argument: I have two stationary data vectors y and x of length 201: y <-

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

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

David Stoffer describes some challenges with R's output when fitting ARIMA models for different orders (see Issue 2 at http://www.stat.pitt.edu/stoffer/tsa2/Rissues.htm). R doesn't fit an intercept in the model if there is any differencing. David describes a workaround using the xreg parameter to force R to calculate an intercept. Assume I have a variable y and 3 explanatory variables a,

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''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)

2009/6/12 Bob Wilson <bob.wilson at apple.com> > Thanks, this should be useful. What problem did you have with svn > revisions after 70786? /tmp/llvm-project.p28262/obj/llvm-gcc-4.2/./gcc/xgcc -B/tmp/llvm-project.p28262/obj/llvm-gcc-4.2/./gcc/ -B/tmp/llvm-73246/llvm-project/x86_64-unknown-linux-gnu/arm-none-linux-gnueabi/llvm-gcc-4.2/arm-none-linux-gnueabi/bin/

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 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