> Try http://finzi.psych.upenn.edu/R/library/nlts/html/spec.lomb.html or > http://finzi.psych.upenn.edu/R/library/cts/html/spec.ls.html (do > RSiteSearch("Lomb periodogram") -- > the Lomb periodogram does a discrete (although not fast) Fourier > transform of unevenly sampled (1D/time-series) data, accounting for > the sampling distribution of points (which will the bias the results > if you try to do a naive Fourier sum). Thanks Ben, that looks like a good start point.
Stephen, my aim are neither spline nor linear approximation but something in the line of matlab's interpfft I do have the vibrational spectrum. Such spectra are frequently computed by ft from their (measured) interferograms. I.e. if you use an FT-spectrometer. However, the spectra can also be measured directly with a dispersive instrument. The difference between neighbouring frequencies of such spectra varies over the spectrum. E.g. I measure from 600 cm^-1 to 1800 cm^-1: at 600 cm^-1 I have a data point spacing of 1.04 cm^-1, while at 1800 cm^-1 it is only 0.85 cm^-1. So doing a ft (like spec.pgram ()) only on the signal means that I do not use periodic functions (sin x), but something rather like sin (x^2) - the sinus changes its frequency. This does not help. The idea is to calculate the interferogram (space or time domain) taking into account this variation of delta nu. Then do a backtransform to evenly spaced frequencies. The next step will then be to do other interesting things like downsampling, denoising etc. using the interferogram. Thanks, Claudia -- Claudia Beleites Dipartimento dei Materiali e delle Risorse Naturali Università degli Studi di Trieste Via Alfonso Valerio 6/a I-34127 Trieste phone: +39 (0 40) 5 58-34 47 email: [EMAIL PROTECTED] ______________________________________________ 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.
