Preface: this is a statistical question more than an R question. I have a vector of numbers (assume a regular time series). Within this time series, I have a set of regions of interest (all of different lengths) that I want to compare against a "baseline" (which is known). There is some autocorrelation involved. I would like to determine the "significance" of the regions as judged by their length and relative height from the baseline. I could do a simple t-test or something like that, but this seems to be too sensitive (probably due to dependency between adjacent observations). I have thought about Hidden Markov Models, but I don't know the number of states. Any other ideas?
Thanks, Sean ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
