similar to: Fourier Analysis and Curve Fitting 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

Hello R community, Does anyone know of a package that will perform cycle regression analysis? I have searched the R-help archives etc. but have come up with nothing so far. If I am unable to find an existing R package to do so, is there anyone familiar with fitting sine functions to data. My problem is this: I have a long time-series of daily SWE estimates (SWE = snow water equivalence, or

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.

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

Hello, In doing a series of non-linear estimations of a function which is a sum of a varying number of sinusoids, I would like to "autogenerate" the arguments needed by nls() depending on that number. For example, when there are two sinusoids: > nls( y ~ mu + A1 * cos(2*pi*f1*x - P1) + A2 * cos(2*pi*f2*x - P2), data = some.xy.data, start = list( mu=some.value0,

On Thu, 2005-01-13 at 12:42 -0500, Jean-Marc Valin wrote: > Le jeudi 13 janvier 2005 ? 10:59 -0500, Jared Whitby a ?crit : > > Interestingly enough.. I started playing around with preprocessing > > options in 1.1.6 and happened upon the denoise filter > > (SPEEX_PREPROCESS_SET_DENOISE). When i run the test tone using that > > option it is completely filtered out and I

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, 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 list, I'm wondering if anyone can help me calculate the deviance of either a zeroinfl or hurdle model from package pscl? Even if someone could point me to the correct formula for calculating the deviance, I could do the rest on my own. I am trying to calculate a pseudo-R-squared measure based on the R^{2}_{DEV} of [1], so I need to be able to calculate the deviance of the full and null

Dear List, I am looking for an efficient method for replacing values in a data.frame conditional on the values of a separate data.frame. Here is my scenario: I have a data.frame (A) with say 1000 columns, and 365 rows. Each cell in the data.frame has either valid value, or NA. I have an additional data.frame (B) with the same number of rows and columns, with valid values in all cells. What I

Dear list, I am trying to plot a radial dendrogram using the ape package, which requires my data to be of class 'phylo'. Currently I have my dendrogram stored as an object of class 'dendrogram' which was produced from an outside bit of C code, but was made into an object of class 'igraph.eigenc' and converted to a dendrogram using 'as.dendrogram()' from the igraph

Dear list, I have been comparing the outputs of two packages for latent class regression, namely 'flexmix', and 'mmlcr'. What I have noticed is that the flexmix package appears to come up with a much better fit than the mmlcr package (based on logLik, AIC, BIC, and visual inspection). Has anyone else observed such behaviour? Has anyone else been successful in using the mmlcr

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hi I have 10.000 simulations for a sensitivity analysis. I have done a few sensitivity analysis for different response variables already, but now, as most of the simulations (if not all) show some cyclic behaviour, see how the independent input parameter influence the frequency of the cyclic changes and "how cyclic" they actually are. So

Interestingly enough.. I started playing around with preprocessing options in 1.1.6 and happened upon the denoise filter (SPEEX_PREPROCESS_SET_DENOISE). When i run the test tone using that option it is completely filtered out and I just get (complete) silence. When the test tone is intermixed with regular voice I only get the voice. So while i still don't quite understand why the test tone

Hello all, I am trying out the echo cancellation of Speex (1.2beta2) on Windows XP. I use the Windows Media API (i.e. waveInOpen, waveOutOpen etc) for playback and capture, but I cannot make echo cancellation works in my use case. Here is a description of what I tried: (the sound is in 8kHz and 16 bits per sample, the frame size is 240, tail_length is long enough to cover the far end to near end

Hello, I have done some research about breakpoints (I am not a statistician) and I found out about the breakpoint, strucchange and segmented packages in R allowing to find breakpoints assuming linear model. However, I would like to fit a periodic time series with a non linear (periodic) model, and I was wondering how I could find breakpoints for this model in R. Is it even possible ? My model

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

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

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