Comparing Time Series
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 <nathan.3073 at gmail.com> 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.
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-- Brian D. Ripley, ripley at stats.ox.ac.uk 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 at 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 at 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.