similar to: Fourier descriptors created in a loop

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-help members, To whom it may concern, our research group is conducting a study to evaluate the predictive value of 24 hour blood pressure variability. We are looking for an R routine that performs a fast Fourier transform spectral analysis (with an output of the approximation function of the Fourier and estimates the validity of the model for the various harmonics). Thanks Vittorio

I did a fourier transform on a function in time domain to get the following functions in frequency domain (in latex): $Y_1[\omega] = \frac{1}{1-\phi_1 e^{-jw}}$ $Y_2[\omega] = \frac{1}{1-(\phi_1 + \phi_2)e^{-jw} +\phi_1\phi_2e^{-2jw}}$ How do I find the spectrum of this function for given $\phi_1$ and $\phi_2$ coefficients and in the discretization interval $w = [-\pi:.1*\pi: \pi]$? Then, how

Dear all, I work with (vibrational) spectra: some kind of intensity (I) over frequency (nu), wavelength or the like. I want to do fourier transform for interpolation, smoothing, etc. My problem is that the spectra are often irregularly spaced in nu: the difference between 2 neighbouring nu varies across the spectrum, and data points may be missing. Searching for discrete fourier transform

Hello, I have a series and I need to run a Fourier Transform for that series. I have done that using the function fft from stats package. However I am not sure whether the result I am getting is correct or not. Seems that the first value of the Fourier Transform list is the sum of all elements of the given series and all the following numbers represent a palindromic series for some how. I have

Dear UseRs, i have a matrix of 365 rows and 444 columns. i drew each column of this matrix against the number of days in a year, which are obviously 365. now i have 444 curves and i want to Use Fourier analysis for the approximation of the average values. does anyone know how to do it? any help in this regards will be deeply appreciated... regards eliza [[alternative HTML version

Hello, I will try to explain the problem, sorry if it will be a little long... I'm using R to analyze results of cyclic mechanical testing, like this: - apply quasi-sinusoidal load - measure quasi-sinusoidal vertical and horizontal deformations (quasi-sinusoidal load means that load "should be" sinusoidal, but testing machine puts in some noise...) I enclose a sample of data at

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

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]]

Dear listers In R, if I have a sequence x(t), t=1,...N, fft(x) is actually giving us sum(x(t)exp(-i*omega*t)) at fourier frequency omega= 2*pi*i/N, i=0,1,...(N-1). The question is if I want to calculate sum(x(t)exp(-i*2*omega*t)), how can I do it? thanks a lot! ------------------------------- liyun (Lauren) Ma Dept of Statistics North Carolina State University

This posting has nothing to do with R (except maybe that I am using R very heavily in writing the paper to which the question pertains.) I simply wish to draw upon the impressive knowledge and wisdom of the R community. Since this question is way off topic, if anybody has the urge to reply, they should probably email me directly: rolf at math.unb.ca rather than via this list. My question

List, I am trying to apply some digital signal analysis methods to IPv4 networks. Specifically, I have had some success using the Fast Fourier Transform in R to find periodic events in IPv4 network traffic by producing periodograms. I store network traffic in a mysql database so I have been using RMySQL to generate a data frame of [timestamp,events] (the FFT is run on the vector of events).

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

I'm doing convolutions in the frequency domain and need to know the layout of the Fourier modes returned by fft. (This is leading up to a more involved question about moment generating functions, but I need to know if I've got this part correct first.) I think in 1D the pattern is: 0 1 2 3 -2 1 (even) 0 1 2 3 -3 2 1 (odd) In 2D is it simply (for a square matrix): 0 1 2 -1 (horizontal)

Hi Guys, I had a monthly time series's data of land temperature from 1980 to 2008. After plotting a scatter diagram, it seems that annually, there is a semi sinusoidal cycle. How do I run Fourier's series to the data so that I can fit model on it? I am really sorry for my question sound stupid, but I just don't know where to start. I am desperately looking for help from you guys.

Hi All, I found "mvfft" in R and "fft2" in Matlab give different result and can't figure out why. My example is: In R: > matrix(c(1,4,2,20), nrow=2) [,1] [,2] [1,] 1 2 [2,] 4 20 > mvfft(matrix(c(1,4,2,20), nrow=2)) [,1] [,2] [1,] 5+0i 22+0i [2,] -3+0i -18+0i In Matlab: >fft2([1,2;4,20]) ans= 27 -17 -21 15 Does any function in R

well if you want to find the spectral density aka what frequencies explain most of the variance then I would suggest the spectral density. This can be implemented with spec.pgram(). This is conducted with the fast fourier transform algorithm. a<-ts(data, frequency = 1) #make the time series with 365readings/365days ?spec.pgram and you should be able to take it from here This will

Dear List, I am attempting to perform a harmonic analysis on a time series of snow depth, in which the annual curve is essentially asymmetric (i.e. snow accumulates slowly over time, and the subsequent melt occurs relatively rapidly). I am trying to fit a curve to the data, however, the actual frequency is unknown. I have been trying to follow the methods in Peter Bloomfields text

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

Greetings, I have the following? Problem: Given k (=10) discrete independent random variables X_i with n_i (= 5 to 20) values each,compute quantiles of the distribution of the sum X = X_1+...+X_k. Here X has n=n_1 x n_2 ... n_k distinct values which is too large to list them all together with their probabilities. I tried several approaches: (A) Convolution: each X_j is approximated with