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 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 usable for ts-like time domain and spectral analysis as per Stoffer?
Another way I was pondering is to map the above to a an artificial index 1:n and consider it multivariate timeseries. Is it something done in irregular timeseries analysis?
Cheers, Alexy ______________________________________________ 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.
