similar to: three related time series with different resolutions

Hi, I have some general questions about statistical analysis for a research dataset and a request for advice on using R and associated packages for a valid analysis of this data. I can only pose the problem as how to run multiple ANOVA tests on time series data, with reasonable controls of the family-wise error rate. If we run analysis at many small sections of a long time-series, the Type-I

I'm collaborating with and electronic musician to experiment on the production of music from number sequences. As I'm an R user I started playing around with the sound library and I found it very useful. However there are several things I do not understand (I'm not an expert in acustic nor audio signal treatment). The first thing I'd like to understand is: let s be a normalized

The following is my R script which I am struggling with to assess ICESat data..perhaps it is the ID_min or ID_max that is wrong? I don't know, any help would be greatly appreciated :( # OPTIONS - CHANGE THESE VARIABLES IF NEEDED\par ######################################################################\par \par icesatfile <-

Hi Jim, First of all - thanks, turning the highpass filter off was what I needed, and the waveforms match now. But, when i did the PESQ tests again I found an interesting result : version 1.0.5 still got a slightly better average score, but the standard deviation on version 1.2 beta1 was much smaller. The cause for that is this - on some samples versions 1.0.5 and 1.2beta2 produced a single

Hi, I have been using speex version 1.0.5 on a text-to-speech program. Recently I upgraded to version 1.2beta1 and noticed that the waveform the I got after encoding and decoding on the new versions (beta1,beta2) is much more different than the original than on version 1.0.5. I also ran a PESQ comparison test on 700 voice samples and got better results in the older version (I used quality 9, and

I would be grateful for advice about the following problem. It's not directly R-related, but I'm hoping that R will help me analyse the following data. I have a table which indicates the progression of a certain age-related disease. At a certain point in time, a population was sampled; and I have measurements for the age of each individual, and their disease stage. (Disease stage is an

Danardono <daodao99 at student.umu.se> wrote: > > While waiting for 2.1, for those who need function[s] for this > survival-splitting business, as I do, this 'survcut' function below > might be helpful. > It is not an elegant nor efficient function but it works, at least for > some examples below. > Ditto the following, for the case where there are multiple

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I am specifically using Celt Wideband (48kHz) over WiFi multicast that naturally leads to lost packets and am trying to minimize the impact to the audio. I implemented PLC but the audio it produces is robotic. Have I implemented PLC correctly? Checking the waveform it is using the previous received waveform to fill in a missing packet but not the full waveform so it has to repeat. Basically,

Hello, I am trying to install R packages under linux, some of the packages can not be installed and I got the following error, could anybody give me suggestion on where the problem is and how to fix it? Thanks-e > .libPaths() [1] "/usr/lib64/R/library" [2] "/usr/share/R/library" [3]

On Aug 7, 2009, at 21:48, Didier Dambrin wrote: > FLAC doesn't preserve every chunk? I thought it did. I only gave a > quick try > but it seemed to have preserved even the most obscure chunks. > Let me check: it even seems to preserve "MIDI note associated to > marker", > which is a very unknown metadata used by SoundForge (& even defined > in a >

How can I change the position of the ylab, after enlarging the margins with par(mar=...)? Here is the relevant code snippet ---- par(mar=c(5.1,5.1,4.1,2.1)) plot(c(1979,2003),c(40,50),ylim=c(1,73),lab=c(20,10,1),pch=21,col='blue',bg='blue',axes=FALSE,xlab="Years",ylab="Onset/Withdrawl Date",font.lab=2) box() axis(1,las=2)

I am puzzled by a filtering problem using fft(). I don't blame R. I have a waveform y consisting of the sum of 2 sinewaves having freqs f1 and f2. I do s = fft() of y. Remove s's spike at freq=f2 Do inverse fft on s. The resulting waveform still has a lot of f2 in it! But the filtering should have removed it all. What is going on, and how to fix?? Thanks very much for any help. Bill

I am writing to get a better handle on a warning I am getting from a coxph analysis I am doing. I am analysing age of onset of dementia *after* the onset of parkinson disease. My data looks like: age.park age.dem age.death censor x1 x2 x3 x4 1 76 87 88 0 16 33 E3 E3 2 75 84 84 0 33 36 E3 E3 3 77 81 81 1 NA NA

I have a normal backup phone (and an alarm panel) sharing the POTS line with the Digium X101P FXO: | | Wall |>---+------X101P FXO as Zap/5 | | | Phone & Alarm Whenever the Phone is used, Asterisk sees a 'false ring' signal immediately when the phone is hung up. The Alarm panel dials out nightly at around 1AM, and each time it completes the call, Asterisk

Hi all! I would like to use Ogg-Vorbis to encode a non audio waveform. My waveform is in .wav format, on 16 bit mono, with frequency range from 100Hz to 100MHz. It's about 100MB lenght. I need to compact it with lossy for net transfer. Is there something like this, already done, that can help me ?? How can I measure the distortion that Vorbis introduce? I'm sorry for my bad english.

Dear All, Writing sooner than I thought I'd need to. I'm using R 2.4 on Mac OS X, with RODBC, PostgreSQL 8.1 and Actual's ODBC driver. I have all my data in Filemaker 8.5, but it is automatically exported into PostgreSQL for analysis as Filemaker's ODBC and JDBC access is awful, slow and has a tendency to crash. I have disability data where for each patient there is a survival

Hello, I would like to compress some data, stored in a Numpy Array (Python) with something like (*): flac.compress(my_array) without having to put data in a .wav file, without having to deal with containers, etc., i.e. : *raw data in / raw data out* Do you have an idea on how to do that with FLAC? This could be useful for audio data of course (stored in simple arrays), but also for other kind

Dear fellow R users, I am replacing elements of a list like so: pulse_subset[[1:20]]=unlist(pulse[i])[1:20] where pulse is a list of lists, and pulse [i] has >20 values. This gives the error "Recursive Indexing failed at level 2". But, interestingly this instruction is part of a loop which has gone through about 200,000 iterations before giving this error. Actual code: >

I have Asterisk configured to record calls. Both in and out record ok but SoxMix fails to join the two files. The error from the CLI is as follows: Execute of ( nice -n 19 soxmix /var/spool/asterisk/monitor/Support-in.wav /var/spool/asterisk/monitor/Support-out.wav /var/spool/asterisk/monitor/Support.wav && rm -f /var/spool/asterisk/monitor/Support-* ) & failed. If I run exactly the