You could look at the dtw package. If x and y are two time series, dtw(x, y)$distance returns the distance between them in the sense discussed in the package.
On Mon, Mar 31, 2008 at 8:37 AM, nathan3073 <[EMAIL PROTECTED]> wrote: > > It is a reaction time experiment. My program will display 25 circles, > arranged in a 5x5 square. The program will light one circle at a time, which > the subject should click ASAP. The time interval between two lighting is > 1.5s. If the subject fails to click in approriate time, the data will be > considered missing. > > The one I want to explore is the relationship between intellegence and the > ability to recognize visual stimuli regularity. I arrange the experiment so > there will be 4 repeated pattern. At last, after all pattern have been > displayed, my program will light the circle randomly. > > I want to check the time series plots, in order to clarify my hypothesis > that the 'smart' and the 'average' deal with stimuli in a different way. For > example, because of 'smart' people is known to be able to recognize > regularity faster, we may expect their plot to decline quite rapidly. But, > because of their automation, we may also expect that they will find some > difficulties to adapt when the pattern has changed. The adaptation > difficulty may be represented (hopefully) by an increasing reaction time. > > I think to check every subject's plot, and determine their ARIMA(p,d,q) > model. Then, if they all follow same ARIMA model, obviously my hypothesis is > wrong, and I may conclude that there are no differences in the way subject > deal with stimuli. But, if let's say 20 subject follow ARIMA(1,0,1) and the > others follow ARIMA(0,0,2) I can say that there are differences in the > subject's cognitive ability for dealing with stimuli. For now, I set aside > what the differences is and its psychological explanation. > > The problem is, it will be very frustating to have 200 subjects and > determine approriate ARIMA model for each plot. So, there're only 2 ways > left. One, I reduce the number of subjects to manageable quantity, let's say > 30 subjects. Or two, I know method(s) that make me possible to analyze > multiple time series plot, and say whether they follow same or different > model. > > Thank you, > regards, > Nathanael > > PS: please forgive grammatical error > > > > Prof Brian Ripley wrote: > > > > Surely you need the insight before choosing a package? > > > > What is the problem you are trying to solve? There are many different > > aspects of time series which could be of interest, and we have no idea > > which are relevant to your problem. > > > > On Sun, 30 Mar 2008, nathan3073 wrote: > > > >> > >> Dear All, > >> I need to compare hundreds (about 200-300) of time series. Would anyone > >> tell > >> me how to do this in R? If R has no package for doing this, can I get > >> some > >> insight what method I should use? > >> > >> best regards, > >> Nathanael Gratias > >> -- > >> View this message in context: > >> http://www.nabble.com/Comparing-Time-Series-tp16392632p16392632.html > >> Sent from the R help mailing list archive at Nabble.com. > >> > >> ______________________________________________ > >> 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. > >> > > > > -- > > Brian D. Ripley, [EMAIL PROTECTED] > > Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ > > University of Oxford, Tel: +44 1865 272861 (self) > > 1 South Parks Road, +44 1865 272866 (PA) > > Oxford OX1 3TG, UK Fax: +44 1865 272595 > > > > ______________________________________________ > > 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. > > > > > > -- > View this message in context: > http://www.nabble.com/Comparing-Time-Series-tp16392632p16396039.html > > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > 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. > ______________________________________________ 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.
