-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 On 14/04/11 11:57, Mike Marchywka wrote: > > > > > > > > > > > ---------------------------------------- >> Date: Thu, 14 Apr 2011 11:29:23 +0200 >> From: r.m.k...@gmail.com >> To: r-help@r-project.org >> Subject: [R] Identify period length of time series automatically? >> >> -----BEGIN PGP SIGNED MESSAGE----- >> Hash: SHA1 >> >> Hi >> >> I have 10.000 simulations for a sensitivity analysis. I have done a few >> sensitivity analysis for different response variables already, >> but now, as most of the simulations (if not all) show some cyclic >> behaviour, see how the independent input parameter influence the >> frequency of the cyclic changes and "how cyclic" they actually are. >> >> So effectively, I have 39 values, and I want to identify automatically >> the frequency / period length of the series and a kind of a measure on >> "how cyclic" the series is.
Hi Mike, thanks for your answer - it confirms my fears ... > > Probably google "Digital Signal Processing" or Fourier transform. > From this, you resolve your time series into sinusoids of various components > and you can separate peaks in line spectra from background noise. > Depending on what you consider to be "cyclic" the analysis details > will vary. If you look at things like amplitude and frequncy modulation > of one sine wave with another and various relationships between carrier and > modulation frequency, you can get some ideas of what to look for in spectra. That is what I thought as well. As I have no idea about fourier analysis, could you give me a small example in R, which gives me the frequencies of the resulting sin waves after a fourier transformation? I only see large matrices as return values when using e.g. fft(). > > Alternatively, you can try to define exactly what you mean by "cyclic" > and maybe make a better transform that discriminates that from acyclic > but offhand I would suggest FFT and various tests on the spectra. the shape of the fluctuations can be quite different - so no common pattern there. > > > Just off hand I'm not sure that 39 points would be a lot to go on > but you can simulate some examples in R quite easily if you know > what the data looks like in various cases you think may exist. Well - the data is over a year summed up data from daily data points, so I could easily go to daily data, which would be 365*39. But that would make the analysis probably more difficult, as I have seasonal fluctuations, and fluctuations over several years (1, 2, 3, 4, ...?; depending on the parameters used for the simulation). Any ideas on how to do this in R? I have the feeling, that the quesion id more difficult then I thought... Rainer > > > > > >> >> How can I do that automatically without individual checking? I do not >> want to do an eyeball assessment for 10.000 time series.... >> >> Thanks, >> >> Rainer >> >> - -- >> Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation >> Biology, UCT), Dipl. Phys. (Germany) >> >> Centre of Excellence for Invasion Biology >> Stellenbosch University >> South Africa > > - -- Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation Biology, UCT), Dipl. Phys. (Germany) Centre of Excellence for Invasion Biology Stellenbosch University South Africa Tel : +33 - (0)9 53 10 27 44 Cell: +33 - (0)6 85 62 59 98 Fax : +33 - (0)9 58 10 27 44 Fax (D): +49 - (0)3 21 21 25 22 44 email: rai...@krugs.de Skype: RMkrug -----BEGIN PGP SIGNATURE----- Version: GnuPG v1.4.10 (GNU/Linux) Comment: Using GnuPG with Mozilla - http://enigmail.mozdev.org/ iEYEARECAAYFAk2mz5QACgkQoYgNqgF2egqZ8QCfZrtSmYczWo+Gq9NgY25mtP5Q LHwAn3qaWKoo2wkc4pjTe9skZhcW7UL+ =4uTI -----END PGP SIGNATURE----- ______________________________________________ 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.
