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Hi, I have tried compiling the latest cvs version of dovecot on my FreeBSD 5.2.1-release box with the ports version of vpopmail: 5.4.3_1. In the configuration file I have two auth paragraphs, one for passwd authentication and one for vpopmail-auth: auth vpopmail { mechanisms = plain userdb = vpopmail passdb = vpopmail user = vpopmail } But the vpopmail dosn'nt work. I got the

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, We have a new 24-core Dell PowerEdge R905 server with 128GB's RAM. The 64 bits version of Fedora 12 lists the correct amount of 128GB, CentOS only finds 32GB (and so does Scientific Linux). I would much prefer to use CentOS (most of the software we use is specifically designed for CentOS). Does anyone know what is causing this/how to fix it? Many Thanks, Diederick -------------- next

Hi, Has anyone been able to successfully install R on CentOS5.4? I am having problems with dependencies.... perl is installed. Cheers, Diederick --> Finished Dependency Resolution R-core-2.10.0-2.el5.x86_64 from R-project has depsolving problems --> Missing Dependency: perl(File::Copy::Recursive) is needed by package R-core-2.10.0-2.el5.x86_64 (R-project) -------------- next part

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)

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 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

Greetings -- I've got some sensor data of the form t1_1, t1_2 t2_1, t2_2 ... tN_1,tN_2 -- time intervals measuring starts and stops of sensor activity. I'd like to see whether there's any regularity in it. Seems natural to consider these data timeseries -- except most of the timeseries packages and models assume regular ones, with a fixed frequency. I wonder what's a

When arima is used to fit a time series, the output gives an estimate of the mean of the series, but calls it the intercept. For example, if x(t) = a + b x(t-1) + w(t) is a stationary AR(1) and w(t) is white noise, then mu = a + b mu, or a = mu (1-b), where mu = E(x(t)). Unless b=0, the mean mu and the intercept a are not the same. Here's a quick R example: > x =

Sorry for reporting this again, but I didn't notice that there was a response. The response to PR#8231 is "This is a matter of opinion!" First, I find this response arrogant and dismissive and I would ask for a second opinion. Second, the use of the term "intercept" - whether or not you think is "a matter of opinion" - is MISLEADING. Why do you want to

Hi All, I have a very simple question about a time series object: how to access values for a particular year and quarter (say)? Suppose, following http://www.stat.pitt.edu/stoffer/tsa2/R_time_series_quick_fix.htm I have read in data as a time series; here is how it looks. * Qtr1 Qtr2 Qtr3 Qtr4 1960 0.71 0.63 0.85 0.44 1961 0.61 0.69 0.92 0.55 . . . . .

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

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,

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 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

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

Hi, Following convention below: y(t) = Ax(t)+Bu(t)+eps(t) # observation eq x(t) = Cx(t-1)+Du(t)+eta(t) # state eq I modified the following routine (which I copied from: http://www.stat.pitt.edu/stoffer/tsa2/Rcode/Kall.R) to accommodate u(t), an exogenous input to the system. for (i in 2:N){ xp[[i]]=C%*%xf[[i-1]] Pp[[i]]=C%*%Pf[[i-1]]%*%t(C)+Q siginv=A[[i]]%*%Pp[[i]]%*%t(A[[i]])+R

I am having a hard time interpreting the phase and coherency plots. x is two timeseries that occur at the same time i.e. a b 1 11.2 12.3 16 11.3 12.4 31 11.4 12.5 46 11.5 12.6 ...etc even though my example is does not show this they are oscillating at more or less the same frequency just shifted by t=x (imagine two sine waves offset with the 2nd sine

Hi, I am trying to learn time series, and I am attending a colleague's course on Econometrics. However, he uses e-views, and I use R. I am trying to reproduce his examples in R, but I am having problems specifying a AR(1) model. Would anyone help me with my code? Thanks in advance! Reproducible code follows: download.file("https://sites.google.com/a/proxima.adm.br/main/ex_32.csv