search for: spectrums

Why is class(spectrum[["Ion"]]) after this "factor"? spectrum <- cbind(spectrum,Ion=rep("", nrow(spectrum)),Deviation.AMU=rep(0.0, nrow(spectrum))) slowly going crazy ... Joh

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(

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

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

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

I have mad a for loop to try and output values which i have named spectrum. However, I cannot seem to get the answers to come out as a vector which is what i need. They come out as separate values which I am then unable to join together. Thank you for(f in seq(0,0.5,0.1)) { sigmasqaured <- 1 i = complex(real = 0, imaginary = 1) spectrum <-

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, I am having some problem with new version of GlusterFS-2.0.1 while copying using "apache" user. sudo -u apache cp -pvf zip/* test/ getting the message cp: getting attribute `trusted.glusterfs.afr.data-pending' of `zip/speccok1ma131231824637.zip': Operation not permitted `zip/speccok1ma131231824776.zip' -> `test/speccok1ma131231824776.zip' No problem while

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.

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

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 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

Hello, I'm still a newbie user and struggling to automate some analyses from SigmaPlot using R. R is a great help for me so far! But the following problem makes me go nuts. I have two spectra, both have to be fitted to reference data. Problem: the both spectra are connected in some way: the stoichiometry of coefficients "cytf.v"/"cytb.v" is 1/2. {{In the SigmaPlot

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

Greetings, I would like to estimate a spectral coherence between two timeseries. The stats : spectrum() returns a coh matrix which estimates coherence (squared). A basic test which from which i expect near-zero coherence: x = rnorm(500) y = rnorm(500) xts = ts(x, frequency = 10) yts = ts(y, frequency = 10) gxy = spectrum( cbind( xts, yts ) ) plot( gxy $ freq, gxy $

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

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

Hi, Are there any functions in R that could be used to estimate the phase-shift between two semi-sinusoidal vectors? Here is what I have tried so far, using the spectrum() function -- possibly incorrectly: # generate some fake data, normalized to unit circle x <- jitter(seq(-2*pi, 2*pi, by=0.1), amount=pi/8) # functions defining two out-of-phase phenomena f1 <- function(x)

Dear useRs, I have a curve which is a mixture of Gaussian curves (for example UV emission or absorption spectrum). Do you have any suggestions how to implement searching for optimal set of Gaussian peaks to fit the curve? I know that it is very complex problem, but maybe it is a possibility to do it? First supposement is to use a nls() with very large functions, and compare AIC value, but it is

Hi, i want to parse a XML-File. I made some Tutorial but with my special Format it don't work. An Example of my format: <?xml version="1.0" encoding="ISO-8859-1"?> <mzML xmlns="http://psi.hupo.org/ms/mzml" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://psi.hupo.org/ms/mzml