[R] Comparing Time Series

[Gabor Grothendieck]

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.
> >>
> >> ______________________________________________
> >> 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.
> >>
> >
> > --
> > 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.
>