similar to: how to smooth timeseries without the lagging?

Hello All, I wanted to perform a fourier transform on high frequency financial data. I have searched and have not found much on this topic for R. I was wondering if anyone has used any libraries for it or have come across any papers I may read. Many Thanks, Neil Gupta [[alternative HTML version deleted]]

I read through the "Writing R Extensions" and the "Debugging in R" website (http://www.stats.uwo.ca/faculty/murdoch/software/debuggingR/), looking for some hints about how to solve the issue of debugging problems encountered during the "R CMD check" process, but nothing seems to be mentioned about addressing issues encountered. Specifically, I am working with the R

I am in the process of dropping the TI DSP lib fft routines into the AEC. Currently, FFTWrap.c uses the USE_SMALLFT and USE_KISS_FFT to select between two packages of FFT routines. ] #ifdef USE_SMALLFT ... #elif defined(USE_KISS_FFT) ... #else #error No other FFT implemented #endif My guess is that every DSP and many other processors will have their own specific FFT and iFFT. What method

Dear R Helpers, Currently I'm working with the ts package of R and created a TimeSerie from pixels extracted from satellite imagery(S10 NDVI data, 10 daily composites). I'm trying to decompose this signal in different signals (seasonal and trend). When testing out the STL method is says => Only univariate timeseries are allowed, but the current Timeserie I'm using is univariate!

>> Yes, I plan to use it in a VoIP environment if I can get latency reduced to >> an acceptable level :) >> The latency depends directly on the overlap parameter, which also controls >> the quality. Higher quality => higher latency. You could set the overlap to >> 0, but that would give you some nasty artifacts. >> You can also resample with smaller block

Hi everyone, I have profiled Opus on AArch64. I just run opus_demo with some pcm files. Following is time proportion of FFT with different bitrate. Bitrate | Time cost by FFT/iFFT 24kb/s | 15% 48kb/s | 15% 96kb/s | 13% Any comment? I want some data close to real application, any suggestion? Thanks, Phil Wang -------------- next part -------------- An HTML attachment was scrubbed... URL:

Viswanath Puttagunta wrote: > Can we please have review on RFCv2? We have quite a few optimizations > (Eg: ifft/mdct_backwards, fixed point fft/ifft mdct_forward/backward > etc) that are in my pipeline that depend on this patch series being > accepted. So, trying to make progress on this... On an armv7l board running Ubuntu, you've broken the build with just --enable-intrinsics

I tracked down the bug to an incorrect use of restrict. I would not consider this a compiler bug: we are lying to the optimizer by telling it that a pointer is restrict when in fact it isn't. This can be fixed like so: diff --git a/celt/mdct.c b/celt/mdct.c index 1634e8e..fa5098c 100644 --- a/celt/mdct.c +++ b/celt/mdct.c @@ -276,8 +276,8 @@ void clt_mdct_backward(const mdct_lookup *l,

Hi R-users: I want to know if there is an easy way to obtain a Fourier Transform form a vector or an array (just like fft does), but with a more density base. I mean, if I have a vector of 512 of length, I want the Fourier Transform to be 1024, or 2048, etc, in length (de u domain). Or should I modify the fft C code to do that? If I want to modify the precision of the fft function, which

Hi! I am using the fft() function the base package to transform some 1d signal. If I use this standar fucntion I get a very huge first fourier coeficient. I think this dues to the handling of the borders of the signal. Usually in fft especially in image processing the signal is simulated to be continuous by adding the signal several times periodically. My question is, is there some function

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

Thanks Jean-Marc. Is there a Speex trunk for the C64xx I can use? Or do I have to figure what options to turn on (in configure) when building the library? Thanks. Regards, Andy Ngo ----- Original Message ---- From: Jean-Marc Valin <jean-marc.valin@usherbrooke.ca> To: ndno72-speex@yahoo.com Cc: jtrantow@ieee.org; speex-dev@xiph.org Sent: Tuesday, December 5, 2006 2:52:02 PM Subject:

I wrote a script that I anticipating seeing a spike at 10Hz with the function 10* sin(2*pi*10*t). I can't figure out why my plots do not show spikes at the frequencies I expect. Am I doing something wrong or is my expectations wrong? require(stats) layout(matrix(c(1,2,3), 3, 1, byrow = TRUE)) #SETUP n <- 256 #nextn(1001) gives next power 2 F <- 100 #Hz -50 to 50 Hz dt

Dear all, Before I can get into serious Fourier analysis of Radon time-series I am practising with 24hour and 24.8hour sinusoids to assist with my interpretation of signals ittributed to tidal input to Radon time series. I am stuck. I have tried researching this to no avail. I am awating a book that should describe fourier transforms in detail and another one that should discuss the R

Dear R Helpers, Is there any literaure available (including R code) on Fast Fourier Transform being used in CreditRisk+? I need to learn how to apply the Fast Fourier Transform. I agree I am too vaue in my question and sincerely apologize for the same, but I am not able to understand as to where do I start for this particular assignment. I tried to search google for CRAN and Fast Fourier

Dear R helpers,   Following is a R script I am using to run the Fast Fourier Transform. The csv files has 10 columns with titles m1, m2, m3 .....m10.     When I use the following commands, I am getting the required results. The probelm is if there are 100 columns, it is not wise to define 100 commands as fk <- ONS$mk and so on. Thus, I need some guidance to write the loop for the STEP A and

Hi List, I'm trying to perform some spectral analysis on a time series, but I've got a few data points missing, so they have NA values. Unfortunately, the fft function doesn't seem to like this, and gives a completely empty result. Other than making up values to fill in the gaps, is there any way I can get around this? Thanks in advance, Steve. PS I haven't spotted anything

Hi, A very simple question. I know that the Fourier transform of a Laplace distribution, with zero mean and variance 2b^2, is equal to 1/(1+(tb)^2). Therefore, the Fourier transform is a positive function (actually is always between 0 and 1). BUT, if I use the fft(alpha) function of R, where alpha is a vector containing 128 values of the probability density function from -2 to 2, I get negative

The characteristic function is the inverse Fourier transform of the distribution function. The characteristic function of a normaly distributed random variable is exp(-t^2/2). x=seq(-2,2,length=100) fft(pnorm(x),inverse=T)/length(x) exp(-x^2/2) Why aren't the inverse fft and the mentioned function the same? Thanks for help, Thomas

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