similar to: Fourier Analysis Help

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]]

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Can someone explain me this spec.pgram effect? Code: period.6<-c(0,0,0,0,0,10,0,0,0,0,0,10,0,0,0,0,0,10,0,0,0,0,0,10,0,0,0,0,0,10 ,0,0,0,0,0,10,0,0,0,0,0,10,0,0,0,0,0,10,0,0,0,0,0,10,0,0,0,0,0,10) period.5<-c(0,0,0,0,0,10,0,0,0,0,10,0,0,0,0,0,0,10,0,0,0,0,10,0,0,0,0,0,0,10 ,0,0,0,0,10,0,0,0,0,0,0,10,0,0,0,0,10,0,0,0,0,0,0,10,0,0,0,0,10,0) par(mfrow=c(2,1))

I have done a fair bit of spectral analysis, and hadn't finished collecting my thoughts for a reply, so hadn't replied yet. What exactly do you mean by normalize? I have not used the functons periodogram or spectrum, however from the description for periodogram it appears that it returns the spectral density, which is already normalized by frequency, so you don't have to worry about

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

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

I have defined a daily timeseries for the 365 days of 2003 issuing: myts = ts(dati[,2:10],frequency=365,) > myts Time Series: Start = c(1, 1) End = c(1, 365) Frequency = 365 and mytime = as.POSIXct(strptime(as.character(dati[,1]),format="%Y-%m-%d")) contains the dates from "2003-01-01" to "2003-12-31" How can I combine mytime and myts in order to list

I receive the following meteo dataset regularly, containing the average daily temperatures (tMedia) of a certain month for 24 selected meteo-stations (COD_WMO) whose human-readable names are in (NOME). str(tabella) `data.frame': 1038 obs. of 4 variables: $ COD_WMO: int 16045 16045 16045 16045 16045 16045 16045 16045 16045 16045 ... $ NOME : Factor w/ 24 levels

I downloaded the latest R-2.1.0 tarball from cran (the one of 18/4/05) to compile it under FreeBSD. Take into account that I compiled R-2.0.1 in the same machine and OS like a charme, flawlessly and at the very fiirst shot. Now with R-2.1.0, ./configure doesn't seem to say anything alarming but make stops. Here an extract of both ./configure and make: # ./configure

I have a TDM card in a asterisk machine. I found that once I used it to call out, the call status changed to "connected" even the callee is still ring. How could asterisk distinguish the "ringing" and "connected" in zap channel? thanks.

I usually work with R on a windows querying data through RODBC from a postgresql db on a freebsd machine on my offcie lan. Now I have the chance to use R also on a linux gentoo client box and to connect to the same db. I know that I can install the unixodbc stuff and stick to RODBC, BUT my question is: Is there any more 'linuxish' way of querying a postgresql server from a client?

Context: Windows XP, R 1.8.1 I'm studying Venables-Ripley "MASS" book and having a go at the many examples in library MASS. The code I'm checking (from script ch04.R) now is ...... data(swiss) splom(~ swiss, aspect = "fill", panel = function(x, y, ...) { panel.xyplot(x, y, ...); panel.loess(x, y, ...) } ) which produces an agreable plot with a gray

Context: Windows XP - R 2.0.1 with the latest updated packages (including Rcmdr) I'm trying to load Rcmdr to use the 3d plots (e.g. scatter3d) but here it is what happens: > library(Rcmdr) Loading required package: zoo Loading required package: strucchange Loading required package: sandwich Loading required package: relimp Loading required package: mvtnorm Loading required package:

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

I use linux debian testing for which the latest debianized version of R is 1.8.1. Therefore I installed: r-base-core_1.8.1-0.cran.1_i386.deb r-base-dev_1.8.1-0.cran.1_all.deb r-base-html_1.8.1-0.cran.1_all.deb r-base-latex_1.8.1-0.cran.1_all.deb r-base_1.8.1-0.cran.1_all.deb r-doc-html_1.8.1-0.cran.1_all.deb r-doc-info_1.8.1-0.cran.1_all.deb

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

I'm learning how to use tapply. Now I'm having a go at the following code in which dati contains almost 600 lines, Pot - numeric - are the capacities of power plants and SGruppo - text - the corresponding six technologies ("CCC", "CIC","TGC", "CSC","CPC", "TE"). .....................................................

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

At office I'm cautiously introducing R to be used as the basic statistical program, getting rid of licensed stuff or reducing the amount of it. The aim of R would be to run generic statistical programs built & "consumed" when needed and some static procedure dealing with time-series. Now, we have substantially 3 OS platforms, win xp, linux and freebsd 5.4, on similar PCs (pentium

Hi everyone Can anyone tell me how I normalise a power spectral density (PSD) plot of a periodical time-series. At present I get the graphical output of spectrum VS frequency. What I want to acheive is period VS spectrum? Are these the same things but the x-axis scale needs transformed ? Any help would be greatly appreciated Tom