similar to: Lomb periodograms

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"

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] *

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

Greetings all, I'm working on a project trying to apply fourier analysis to timestamped router logs, using R to perform the analysis. The idea is to determine if any type of traffic (say, outgoing ICMP requests) has strong periodic features because it may indicate a compromise somewhere on the network. The FFT requires all data points to be evenly spaced, but the recorded events do not

Hola a todos, Estoy trabajando con modelos lineales generalizados (GLM), en particular con las funciones glm y anova.glm de R. Tengo una pregunta que es más bien técnica en el sentido estadístico (y un poco Off Topic y probablemente un tanto naive). No tengo claro si es correcto decir análisis de varianza o de devianza al utilizar GLMs, veo que en el help de anova.glm dice análisis de

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

Hello everybody, I recently wrote a "program" that to generate AR1 time series, here the code: #By Jomopo. Junio-2007, Leioa, Vizcaya #This program to create the AR1 syntetic series (one by one) #Where the mean is zero, but the variance of the serie AR1 and #the coef. of AR1 are be changed. If var serie AR1 = 1 then is standarized! #Final version for AR1 time series program #Mon Jul

Hi all, I am trying to do wavelets and I got an error message saying "The length of data is not a power of 2" Is there a way of handing that? or should the data length be exactly the power of 2? I am using R version 2.9.2 (2009-08-24) The is library(wavethresh). wds <- wd(ds$v,filter.number=1) Thanks

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

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]]

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

hello, I have been using the per function in package longmemo to obtain a simple raw periodogram. I am considering to switch to the function spec.pgram since I want to be able to do tapering. To compare both I used spec.pgram with the options as suggested in the documentation of per {longmemo} to make them correspond. Now I have found on a variety of examples that there is a shift between

Dear all, I'm trying to finding the fundamental harmonics (ie. peaks in a periodogram) from a time series (extracted from an mp3). For example, if I look at spectrum(fdeaths, spans = c(3,3)) I'd say the fundamental harmonics are about 1, 2, 3.5 and 4.5 - but how can I extract these automatically? (preferably with some heuristic for choosing the smoothing spans too) I'm aware of

Hi everyone, first of all, I would like to say that I am a newbie in R, so I apologize in advance if my questions seem to be too easy for you. Well, I'm looking for periodicity in histograms. I have histograms of certain phenomenons and I'm asking whether a periodicity exists in these data. So, I make a periodogram with the function spec.pgram. For instance, if I have a histogram h, I

Hello everyone, This is my first time posting to the list, thanks in advance. I am calculating the smoothed periodogram for the residuals of an AR model that I fit to EEG data. The autocorrelation plot of the residuals shows the series is now approximately white (i.e. ACF = 1 at lag 0, and close to 0 for all other lags). I would like to show that the spectrum of the series is also

I have done a fair bit of spectral analysis, and hadn't finished collecting my thoughts for a reply, so hadn't replied yet. What exactly do you mean by normalize? I have not used the functons periodogram or spectrum, however from the description for periodogram it appears that it returns the spectral density, which is already normalized by frequency, so you don't have to worry about

Hello world, I am actually trying to transfer a lecture from Statistica to R and I ran into problems with spectral analysis, I think I just don't get it 8-( (The posting from "FFT, frequs, magnitudes, phases" from 2005 did not enlighten me) As a starter for the students I have a 10year data set of air temperature with daily values and I try to get a periodogram where the annual

Dear All, I am looking for: A software to select the lag length for a lag window spectral estimator. Also, I have a small query in the reprex given below. Background for the above, from the book by Percival and Walden: 1. We are given X_1,...,X_n which is one realization of a stochastic process. 2. We may compute the periodogram using FFT, for example by the function spectrum in R. 3. The