similar to: spectral analysis of time series

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 list, I' m studying FLAC performance, and I'd like to know how much compression can be achieved for different audio files. 1) It seems that for nontonal sound (wideband noise), the compression factor is better than for compound sound (tones + nontonal components), which is typically 2. The reason for this result could be the following: the LPC filter is more suitable for

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

Hello- I'm new to R, coding and stats. (Oh no.) Anyway, I have about 12000 data points in a data.frame (dealing with dimensions and geological stage information for fossil protists) and have plotted them in a basic scatter plot. I also added a boxplot to overlay these points. Each worked fine independently, but when I attempt to superimpose them with add=true, I get a different scale for

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 Can anyone tell me how I normalise a power spectral density (PSD) plot of a periodical time-series. At present I get the graphical output of spectrum VS frequency. What I want to acheive is period VS spectrum? Are these the same things but the x-axis scale needs transformed ? Any help would be greatly appreciated Tom

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

Hi all, I am dealing with paleoceanographic data and I have a C14 time serie and one other variable. I would like to perform a spectral analysis (fft or wavelet) and plot it. Unfortunately I don't know the exact script to do this. Does anybody could send me an example to perform my spectral analysis ? I Thank you David Changez de tête et de tenue tous les jours si vous le voulez !

Please, does anyone know of an R packge to estimate multidimensional spectral measure of coherence within a moving time window ? Some time ago I expeimented with a similar package that performs Cross Spectrum Analysis on the whole signal though. Unluckily I deal with non-stationary signals whose properties change along with time. Therefore estimates can only be made over time periods roughly

Hi, here is a practical problem we would like to solve. In a pneumatic post the acceleration of the capsule is measured and plotted over time. From the graph achieved we would like to derive some kind of statistic value that describes the stress the capsule, or what is in it, is exhibited to. The amount of stress introduced to the capsule will probably depend on two things, the maximum

Dear R Community, I am currently student at the Vienna University of Technology writing my Diploma thesis on causality in time series and doing some analyses of time series in R. I have the following questions: (1) Is there a function in R to estimate the PARTIAL spectral coherence of a multivariate time series? If yes, how does this work? Is there an test in R if the partial spectral

Jan, I'm forwarding this message to the rest of the developers. Hopefully one of them will have a good answer to your question. --------- Does someone want to take this one? Just make sure you copy him on the answer, as he's not on the list. jack. ----- Forwarded message from Jan.Tangring@et.se ----- From: Jan.Tangring@et.se To: jack@icecast.org Subject: spectral band replication

Dear all, Is there any spectral analisys functionality available for R version 3.4.3? Series() functionality doesn't work in this version. Regards Danniel [[alternative HTML version deleted]]

Dear all, I am searching the period of a time series usering R. Is there some lag window functions in R? Could you give me some books about spectral analysis usering R? best wishes, Wang [[alternative HTML version deleted]]

There's a new module in CVS called 'masktest'. I spent the last few weeks writing this program. It can measure masking based on input from people. We need it to obtain better masking curves than we have right now (from Ehmer...). It's not finished yet, but you can get a feeling of what it's supposed to do. It will measure the masking between tone and tone, noise /tone,

Can someone explain me this spec.pgram effect? Code: period.6<-c(0,0,0,0,0,10,0,0,0,0,0,10,0,0,0,0,0,10,0,0,0,0,0,10,0,0,0,0,0,10 ,0,0,0,0,0,10,0,0,0,0,0,10,0,0,0,0,0,10,0,0,0,0,0,10,0,0,0,0,0,10) period.5<-c(0,0,0,0,0,10,0,0,0,0,10,0,0,0,0,0,0,10,0,0,0,0,10,0,0,0,0,0,0,10 ,0,0,0,0,10,0,0,0,0,0,0,10,0,0,0,0,10,0,0,0,0,0,0,10,0,0,0,0,10,0) par(mfrow=c(2,1))

I used the AR modelling written for R (S) on blood pressure and heart rate signals. I used 60 one second samples and a model order of 20. I used the "ar" finction in the "ts" package. Given that blood pressure is measured in mmHg would the spectral density (on the graph displayed be [mmHg]sq/Hz ? And the heart rate is measured in Beats Per Minute (bpm) - so would the

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

This works really well for white noise reduction. However what I've noticed was the amplitudes of normal speech samples also get reduced. Is this something by design, or is there a way to automatically recover the original speech sample volumes ? <p>Thanks. <p>Tongbiao <p>-----Original Message----- From: Jean-Marc Valin [mailto:jean-marc.valin@hermes.usherb.ca] Sent: