similar to: newbie: fourier series for time series data

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

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

Hi Can any one inform me an r package used to fit Cubic M-splines or r functions used to have design and penalty matrices in fitting cubic  M-splines please? Thanks, Tigist [[alternative HTML version deleted]]

Hi, This is the time series data collected from 2001 to 2008 by every month.so,there are 96 entries.I have done basic statistics.I need to find a model fitted to forecast this data.This is the mixedpaper collection for recycling in the campus. 13251 13754 19061 12631 17414 21350 25384 23646 20312 20740 14007 17175 13910 17191 17113 20250 35003 11975 19665 20490 20436

Hi everybody. i have 2 datasets : one with a long grid a lat grid and a bathymetry grid the second one only has the long and lat coordinates. So i want to know the bathymetry associated to the second dataset. I thought it was a good idea to do an interpolation between the two datasets. I find a script doing that on matlab but i want to do it on R. Do you how to do it? for ii =

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

Hi All, Here is the problem: I'm trying to generate a number of Fourier Descriptors figures for an experiment. All I need is that they are created within a loop and saved with sequential names (e.g., s1_1.png, s1_2.png etc..) in my directory. I created a nested loop with a counter for the different amplitudes for the actual shapes and a counter for the file names. This script: *count

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

How reliable is R-Forge? http://r-forge.r-project.org/ It is down now (for me). Reporting "R-Forge Could Not Connect to Database: " I have just started to use it for a project. It has been down for several hours (at least) on different occasions over the last couple of days. Is that common? Will it be more stable soon? Apologies if this is not an appropriate question for R-help. Dave

How reliable is R-Forge? http://r-forge.r-project.org/ It is down now (for me). Reporting "R-Forge Could Not Connect to Database: " I have just started to use it for a project. It has been down for several hours (at least) on different occasions over the last couple of days. Is that common? Will it be more stable soon? Apologies if this is not an appropriate question for R-help. Dave

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]]

Hi there, I'm in desperate need to figure out how to solve this issue. I need to estimate a recursive model for a time series data of asset returns. The dependent variable is the asset return and then I have a set of k variables, a lagged value of the dependent variable (plus an intercept) as regressors. My sample period (monthly observations) starts on Jan 1972. What I need to do is the

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

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 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

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

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 all R gurus out there, Im a kind of newbie to kalman-filters after some research I have found that the dlm package is the easiest to start with. So be patient if some of my questions are too basic. I would like to set up a beta estimation between an asset and a market index using a kalman-filter. Much littarture says it gives superior estimates compared to OLS estimates. So I would like to

I tried to specify a model in dse1 but something isn't right. Anybody have any tips? model<-SS(F=f,G=g,H=h,Q=q,z0=z,P0=p) Error in locateSS(model$R, constants$R, "R", p, p, plist) : The dimension of something in the SS model structure is bad. > dim(f) [1] 5 5 > dim(g) [1] 5 1 > dim(h) [1] 1 5 > dim(q) [1] 5 5 > dim(z) [1] 5 1 > dim(p) [1] 5 5 thanks, Bob

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