search for: stoffer

...onfiguration 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 folowing in the log: Info: auth(vpopmail): vpopmail(stoffer at test.ek.dk): unknown user (stoffer at test.ek.dk) When I ktrace the dovecot process, it seams that it is trying to access the mysql db, but it ignores the settings in ~vpopmail/etc/vpopmail.mysql If I use the ports version of dovecot it works, but of course without the multiple auth capability...

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 output says it's giving you the estimate of the intercept, when, in fact, it's giving you the estimate of the mean. These are NOT the same when an AR term is present. T...

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) This is quite surpr...

...nd 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 HTML version deleted]]

...nd 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 HTML version deleted]]

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 (checke...

...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 good way to apply existing regular timeseries packages to these data, and perhaps try some others? I like David Stoffer's book a lot, yet he uses R's own ts methods (with some extras). I also like the zoo package, which allows for irregular timeseries, yet I'm not sure how to apply the "usual" models to zoo objects -- even though zoo strives to be compatible with ts... Is zoo directly...

...R(1) with mean 10. The "intercept" estimate in this example should be 9.8067*(1-.8704). Either change the output to read "mean" instead of "intercept", or report the intercept instead of the mean. Thanks- David -- -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- David S. Stoffer Department of Statistics University of Pittsburgh Pittsburgh, PA 15260 phone: [412] 624-8496 fax: [412] 648-8814 email: stoffer at pitt.edu web: http://www.stat.pitt.edu/stoffer voice: hey dave

...ally? You don't think that's misleading? Again, I put this to you: Why do you want to MISLEAD the user. Get some other opinions on this if you don't agree with me. Thanks again for your time and sorry for the double report. David -- -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- David S. Stoffer Department of Statistics University of Pittsburgh Pittsburgh, PA 15260 phone: [412] 624-8496 fax: [412] 648-8814 email: stoffer at pitt.edu web: http://www.stat.pitt.edu/stoffer voice: hey dave

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 . . . . . . . . . . 1979 14.04 12.96 14.85 9.99 1980 16.20 14.67 1...

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...

...ink 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. http://lib.stat.cmu.edu/general/stoffer/tsa2/Rissues.htm Thanx in advance. Sachin --------------------------------- [[alternative HTML version deleted]]

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 sig[[i]]=(t(siginv)+siginv)/2 # make sure sig is symmetric siginv=solve(sig[[i]]) # now siginv...

...at more or less the same frequency just shifted by t=x (imagine two sine waves offset with the 2nd sine wave starting at the peak of the first). I would like to know what x is. I think I am looking for the phase shift? The coherency? Cross-spectrum? And I have read the help files, Shumway and Stoffer has a small section on this, I don't have journal access, and I am having trouble finding anything on the internet. s = spec.pgram(x) par(mfrow = c(2,1)) plot(s, plot.type = "coh") plot(s, plot.type = "pha") Can R do the cross-spectrum of two timeseries? How? -- Let...

...D. dependent var 1284.675 # S.E. of regression 22.81029 Akaike info criterion 9.121554 # Sum squared resid 50990.32 Schwarz criterion 9.199231 # Log likelihood -457.6385 F-statistic 158548.1 # Durbin-Watson stat 2.350440 Prob(F-statistic) 0.000000 # following code based on http://www.stat.pitt.edu/stoffer/tsa2/R_time_series_quick_fix.htm # "And now for some regression with autocorrelated errors." # I've tried to follow the example in Pinheiro & Bates (2004), p. 239-244, with no success. gc_ts = ts(ex32[66:166,"gc"]) yd_ts = ts(ex32[66:166,"yd"]) library(nlme)...