similar to: Preparing timestamped data for fourier analysis

Dear time-series specialist: I've got some time series representing measurements from a physical process, like atomic decay data. These time series look almost random, but should hopefully be distinguishable as they were taken under different conditions. I am looking for statistical approaches that are sensitive enough to discriminate between such series of measurements. Preferably, there

Hi, I have recently used the CTS package in order to use the Lomb-Scargle periodogram (spec.ls) function. I have noticed an issue that I hoped you may be able to explain. If a regularly spaced time series has two points removed, one at either side of a single data point (thus making an irregularly spaced time series), a spectrum with a very large peak at the highest frequencies is produced. An

Hello! I tried to contact author of the package, but I got no reply. That is why I write it here. This might be useful for those who were using cts for spectral analysis of non-uniformly spaced data. In file spec.ls.R from cts_1.0-1.tar.gz lines 59-60 are written as pgram[k, i, j] <- 0.5 * ((sum(x[1:length(ti)]* cos(2 * pi * freq.temp[k] * (ti - tao))))^2/sum((cos(2 * pi * freq.temp[k] *

Sorry for the long letter! I have recently started using R. For the start I have tried to repeat examples from Milliken & Johnson "Analysis of Messy Data - Analysis of Covariance", but I can not replicate it in R. The example is chocolate chip experiment. Response variable vas time to dissolve chocolate chip in seconds (time), covariate was time to dissolve butterscotch chip

Hi, Does anyone know the name of the package that includes a function for computing the lomb periodogram on irregular spaced ts data? I saw the package once ~ 1 month ago but cannot find it now ... , Rich

Greetings all, I am using Fourier analysis to search for periodicities in IP network traffic by generating periodograms and then visually examining them for large, distinct peaks. However, in many cases it is not readily apparent where there are periodicities. I have no experience with discrete maths so I've come up against a block here: How do I define what the "noise floor"

hi R users I have a large 1D dataset and some of them is NA value . I found I cound get the spectrum by such a command. ua=c£¨10£¬30 £¬40£¬50£¬NA£© spectrum(ua) and I could not use na.rm just like mean or sd function How could I get the spectrum of ua ? thank you . -- TANG Jie [[alternative HTML version deleted]]

Hi everybody, I am reading the Lomb paper (Lomb, 1976) and I found an interesting equation, and I wish to resolve it using R. I am wondering if anybody has a hint. The equation is: Yis[i] = a*cos((2*pi/T)*(Times[i] - Tau)) + b*sin((2*pi/T)*(Times[i] - Tau)) ... (1) Where T and Tau are constants. I know the "Times" and "Tis" values (in fact these values come from a Time

Background: OS: Linux Mandrake 9.1 release: R 1.9.0 editor: Xemacs 21.4 frontend: ESS 5.1.23 --------------------------------- Colleagues I have two time series (upwelling index and water temperature) of evenly spaced, daily data over 18 months, but the upwelling index series has a gap of about 2 months right in the middle of it. I want to do the acf, pacf, ccf, and a cross-spectral analysis

Dear R users Is there a function in R to make a peridogram for a spectral analysis of unevenlly sampled data?? something like spec.lomb() for S-Plus?? How to plot a vector with unequally spaced time series?? e.g day/month/year V1 03/08/82 0.34 28/08/82 1.42 12/09/82 0.28 20/09/82 0.56 03/10/82 0.85 21/10/82 1.45 thanks -- Marcelo Alexandre Bruno - Pos-graduacao Oceanografia Biologica

Hello to everybody, I just subscribed to this list. I find R a really nice environment for statistical analysis. I started to use it some days ago. I use it at home in my Linux box, but I would like to use it in my institute in my Digital Alpha (my machine runs OSF1 V4.0). I tried to compile the distributed source code, without success due to some errors. And the binary available is in RPM

Readers of this list might be interested in the following commenta about R. In a recent report, by Michael N. Mitchell http://www.ats.ucla.edu/stat/technicalreports/ says about R: "Perhaps the most notable exception to this discussion is R, a language for statistical computing and graphics. R is free to download under the terms of the GNU General Public License (see http://www.r-project.

Dear listers In R, if I have a sequence x(t), t=1,...N, fft(x) is actually giving us sum(x(t)exp(-i*omega*t)) at fourier frequency omega= 2*pi*i/N, i=0,1,...(N-1). The question is if I want to calculate sum(x(t)exp(-i*2*omega*t)), how can I do it? thanks a lot! ------------------------------- liyun (Lauren) Ma Dept of Statistics North Carolina State University

Hello, I have a series and I need to run a Fourier Transform for that series. I have done that using the function fft from stats package. However I am not sure whether the result I am getting is correct or not. Seems that the first value of the Fourier Transform list is the sum of all elements of the given series and all the following numbers represent a palindromic series for some how. I have

This posting has nothing to do with R (except maybe that I am using R very heavily in writing the paper to which the question pertains.) I simply wish to draw upon the impressive knowledge and wisdom of the R community. Since this question is way off topic, if anybody has the urge to reply, they should probably email me directly: rolf at math.unb.ca rather than via this list. My question

List, I am trying to apply some digital signal analysis methods to IPv4 networks. Specifically, I have had some success using the Fast Fourier Transform in R to find periodic events in IPv4 network traffic by producing periodograms. I store network traffic in a mysql database so I have been using RMySQL to generate a data frame of [timestamp,events] (the FFT is run on the vector of events).

Hi All, I found "mvfft" in R and "fft2" in Matlab give different result and can't figure out why. My example is: In R: > matrix(c(1,4,2,20), nrow=2) [,1] [,2] [1,] 1 2 [2,] 4 20 > mvfft(matrix(c(1,4,2,20), nrow=2)) [,1] [,2] [1,] 5+0i 22+0i [2,] -3+0i -18+0i In Matlab: >fft2([1,2;4,20]) ans= 27 -17 -21 15 Does any function in R

I did a fourier transform on a function in time domain to get the following functions in frequency domain (in latex): $Y_1[\omega] = \frac{1}{1-\phi_1 e^{-jw}}$ $Y_2[\omega] = \frac{1}{1-(\phi_1 + \phi_2)e^{-jw} +\phi_1\phi_2e^{-2jw}}$ How do I find the spectrum of this function for given $\phi_1$ and $\phi_2$ coefficients and in the discretization interval $w = [-\pi:.1*\pi: \pi]$? Then, how

Dear UseRs, i have a matrix of 365 rows and 444 columns. i drew each column of this matrix against the number of days in a year, which are obviously 365. now i have 444 curves and i want to Use Fourier analysis for the approximation of the average values. does anyone know how to do it? any help in this regards will be deeply appreciated... regards eliza [[alternative HTML version

2009/5/16 Arnaud Quette <aquette.dev at gmail.com> > > > 2009/5/7 Daniel O'Connor <doconnor at gsoft.com.au> > >> On Wed, 6 May 2009, Arnaud Quette wrote: >> > I think I've found something, but I would need an upsd debug output >> > (level 3) to see what going on the state socket. >> >> I've attached a log for you. >>