similar to: how to analysisi spectrum of a dataset with NA value

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

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

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 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] *

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

Hello. Does anyone know how to generate a power spectrum from the STFT function in package e1071? The output for this function supplies the Fourier coefficients, but I do not know how to relate these back to the power spectrum. Alternatively, if anyone is aware of other packages/functions that perform short time Fourier transforms, that would also be helpful. Thanks. -- View this message in

For the command 'spectrum' I read: The spectrum here is defined with scaling 1/frequency(x), following S-PLUS. This makes the spectral density a density over the range (-frequency(x)/2, +frequency(x)/2], whereas a more common scaling is 2? and range (-0.5, 0.5] (e.g., Bloomfield) or 1 and range (-?, ?]. Forgive my ignorance but I am having a hard time interpreting this. Does this mean

This was an interesting post from another list I'm on. I think that with all of the echo cancellation discussion happening, that someone perhaps might be on the lookout for this type of software, so this post was well-timed for Asterisk uses. It is perhaps the case that those of you working on volume/echo/etc stuff might find this useful towards your goals. JT >To: [snip]

Hi, I'm wondering why the spectrum() phase of quadrature couple isn't purely +/-pi. But mostly, I'm looking for a recommended way to take a 2-D spectrum and convert it into a single complex array. Kindly consider: # 10 Hz sine wave 10 seconds long sampled at 50 Hz deltaT = 1/50 t = seq(0, 10, deltaT) w = 2 * pi * 10 x = ts( sin( w * t ), deltat = deltaT ) y = ts( sin(

hi I plot a series of observation data every minutes in a day as the attachment below plot(wnd,type='l',lty=1,col='red',lwd=1,xlab=xxlab,ylab=yylab,ylim=YY) In the figure, the x-axis tickment is the number of data How can I change it fore example 1h 2h 3h 4h and so on ? -- TANG Jie Email: totangjie at gmail.com Tel: 0086-2154896104 Shanghai Typhoon Institute,China

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

Dear r-help list: In the following R session, I seem to be somehow breaking the spectrum() function, but I'm not sure how. Could somebody please point out my mistake? My apologies if it's something that should be obvious. The mysterious bit is how spectrum(my.ts) at first works, but then later fails with an error message that I find difficult to interpret. I'm running R 1.3.0

hi ,everyone, I have a script shown as below: > bj2=bjerrdata$tyerr[bjyearnum[2]+1:bjyearnum[3]] > length(bj2) [1] 448 while > b=bjyearnum[3] > a=bjyearnum[2]+1 > bj1=bjerrdata$tyerr[a:b] > length(bj1) [1] 169 it is different with bj2 and bj1 . and the array bjyearnum is [1] 0 279 448 633 1021 1365 1813 2237 2839 3314 3798 4157 12 why bj1 is 169 while bj2 is 448

Dear list, I apologies first for my English, hope you will understand well my question. I am working on 1/2 hour piezometric data, time unit is second. They present daily oscillation when using the spectrum() function. What I am really interested in, is to find the amplitude corresponding to this oscillation. I work with a college using Matlab, and although we apply the same methodology, our

hi everyone . Now I want to draw several lines in one frame.And it seems needs more colors except for blue red,black .Where can i found these color name or define some new color ?thank you . -- TANG Jie Email: totangjie@gmail.com Tel: 0086-2154896104 Shanghai Typhoon Institute,China [[alternative HTML version deleted]]

Hi, everyone, I tried to use "spectrum()" or "spec.pgram()" to get a periodogram of a time series but they didn't work. Even the examples given in the help file didn't work (all with the same error message, below). And the 'ts'ibrary was loaded with "library(ts)" or "library("ts"). I also tried library(tseries) but got the same problem.

Dear R users I have two questions about estimating the spectral power of a time series: 1) I came across a funny thing with the following code: data(co2) par(mfrow=c(2,1)) co2.sp1<-spectrum(co2,detrend=T,demean=T,span=3) co2.sp2<-spectrum(co2[1:468],detrend=T,demean=T,span=3) The first plot displays the frequencies ranging from 0 to 6 whearas the second plot displays the same curve but

I am reading some documentation about Cross Spectrum Analysis as a technique to compare spectra. My understanding is that it estimates the correlation strength between quasi-periodic structures embedded in two signals. I believe it may be useful for my signals analysis. I was referred to the R functions that implement this type of analysis. I tried all the examples which generated a series of

Hi everybody! I am searching for an R implementation of multi-scale singular spectrum analysis (SSA), which was introduced by Yiou etal (2000) (Data-adaptive wavelets and multi-scale singular-spectrum analysis) and further described in Ghil etal (2002). For SSA alone I found an package recently published on r-forge: http://r-forge.r-project.org/projects/simsalabim/ I am happy about any