I would first abandon time-domain techniques altogether for irregularly spaced series. The Lomb Scargle periodogram is available for R, here: http://research.stowers-institute.org/efg/2005/LombScargle/R/index.htm.
KeithC. -----Original Message----- From: ravi [mailto:rv...@yahoo.se] Sent: Friday, February 26, 2010 3:05 PM To: r-help@r-project.org Subject: [R] decomposing an irregularly spaced time series Hi, I am interested in decomposing an irregularly spaced time series and getting results similiar to that obtained with the stl command for a regularly spaced time series. I would like to know if any of the time series packages like zoo can be used for this. From my search, I was only able to find some help with the tseries and pastecs passages, But I had difficulty in going the full length even with these packages . Let me explain with my sample code : # Attemts with the functions irts, regul and tsd n<-20 t1 <- runif(n) n1<-(1:n)*1e6 t2<-t1*1e3 t3<-n1+t2 u <- rnorm(n) n2<-rep(1:5,times=4); u<-u+n2 library(tseries) x <- irts(t3, u) # could not find a decomposition method for irts y<-data.frame(day=x$time,val=x$value) y$day<-as.Date(y$day) y$nday<-as.numeric(y$day) y with(y,plot(nday,val,type="b")) library(pastecs) y1<-y$day[1] yf<-"y-m-d" reg.y<-regul(x=as.numeric(y$day),y=y$val,units="days",methods=c("l"), datemin=y1,dateformat=yf,deltat=5) I get the following error message : Error in approx(x, y, xout, method = "linear", rule = rule) : need at least two non-NA values to interpolate I would like to get help on the following points : 1. The actual decomposition is suposed to work with the tsd command. Is it possible to use it without first using regul? 2. Can I succeed with the regul command by a better choice of argument values? My attempts to set rule=2 did not help. 3. Would it be better to first get a regularly spaced time series by interpolation, and then try decompostion with stl? I would appreciate some practical help here. 4.Is it hopeless to attemt decomposition when the irregularity level is high? The series that I am working on is fairly regular in periods interpersed with either breaks or irregular data. I would like to see the trends and seasonal effects there. Is there an alternative method of approaching this task? Thanking you, Ravi ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
