similar to: Periodogram of Schuster

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

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, 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

I am trying to compute the periodicity of a time series. I would like to know which function in R does it. Also, how do I plot a Enright / Chi-square periodogram using R ? ( Enright, J.T., 1965, Journal of Theoret. Biol. 8,426-468) Greatly appreciate your help. Thanks in advance, Sukhaswami Malladi *************************************************************************** The contents

nitish wrote: > > I have a dataset that goes like: dataset = > t |x > 0 |x1 > 1 |x2 > 2 |0 > 3 |0 > 4 |0 > 5 |0 > 6 |x3 > 7 |0 > 8 |0 > 9 |0 > 10 |x4 > > and so on. I wish to detect the periodicity of occurrences. t is in > seconds and x are arbitrary, whose magnitude i am not interested in. I > just wish to get a best

Hello, I'm actually using the "Step" procedure in R for multiple regression analysis. I'm using the stepwise selection which alternates between forward selection and backward elimination (direction "both" in the step procedure). I would like to know which F-levels R is using to enter and then to remove variables? I also would like which is the procedure to change

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

Dear Prof Ripley, First of all, unless you are an english professor, then I do not think you have any business policing language. I'm still very much a student, both in R, and regarding signal analysis. My competence on the subject as compared too your own level of expertise, or my spelling for that matter, may be a contension for you, but it would have been better had you kept that opinion

Dear R-users, I computed a simple mixed models which was: mod<-lmer(nb ~ site + (1|patelle),tr) The output was: Linear mixed-effects model fit by REML Formula: nb ~ site + (1 | patelle) Data: tr AIC BIC logLik MLdeviance REMLdeviance 1157.437 1168.686 -574.7184 1164.523 1149.437 Random effects: Groups Name Variance Std.Dev. patelle

Dear R experts, beginners and everyone else, I'm calculating "cumulative periodogram" using the command "cpgram" [1] from the MASS library. Here is a short example with the "lh" (hormone level) dataset: library(MASS) plot(lh,type="l",ylab="value",xlab="time", main="Hormone Levels (lh)") spectrum(lh,

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

Hi ! I have installed R-2.7.0 64-bits on a computer where the new Ubuntu version (8.04) was installed. This computer is a 3.2 GHz Dual-core with 2 Gb of RAM. To test how fast (I though !) this machine is, I compared two simple matrix manipulations between Ubuntu and my laptop (a MacBook Pro 2.2 GHz with also 2 Gb of RAM under Mac OS X 10.5.2). By the way, I install the normal version of R

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 R-Users, I am doing a research on Time Series, especially on the estimation of the fractional exponent in long memory time series (for those who know). However there are three estimators already built-in the fracdiff package (GPH, Sperio, MLE) I was wondering if there is someone who had used an estimation introduced by P.M. Robinson (related paper: "Log-Periodogram regression of time

Hello, I see some people including myself confused by the different object-oriented approaches in R (S3, S4, OOP, R.oo etc.). Would it be ok to collect examples and solutions for the different OO-packages in one package and add a vignette for documentation? (assuming I find time for this task) I mean in this case the package would not add data or functionality to R or serve as a companion

I need help in typing step by step commands in R software for panel data analysis saibaba

Dear R users, I am having a problem with the main title of a plot. I have written a function returning a plot and I would like that the main title of this plot shows actually the name of the dataset I have used. So, for instance: if my dataset is called Chl, I would like that my plot to be entitled : "Raw periodogram of Chl". I know the function "paste". I suppose I would be

Hi All, I have two time series, each has length 354. I tried to calculate the coherency^2 between them, but the value I got is always 1. On a website, it says: " Note that if the ensemble averaging were to be omitted, the coherency (squared) would be 1, independent of the data". Does any of you know how to specify properly in R in order to get more useful coherency? The examples in

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"