similar to: how calculate seasonal component & cyclic component of time series?

Hi list, I would like to estimate and forecast the seasonal component of a series. My model which uses daily data would be something y t = alpha + beta x SeasComp t + gamma x OtherRegressors t. One approach to this would be use quarterly dummies, another to use a sine function. The first would cause a step change when we move from a season to another; the latter impose too much regularity in

Hi R-help, I'd like to extract the seasonal component of a short timeseries, and was hoping to use stats::decompose. I don't want to decompose the 'trend' component so I thought I should call decompose(x,filter=0). I think I've either misunderstood the filter argument or come upon a bug/feature in decompose. # EXAMPLE

Hi All, a) Is it possible to estimate the strength of seasonality in timeseries data. Say I have monthly mean prices of an ten different assets. I decompose the data using stl() and obtain the seasonal parameter for each month. Is it possible to order the assets based on the strength of seasonality? b) which gives a better estimate on seasonality stl() or a robust linear model like

Hello, I'd like to know how R does calculate each component in the decompose() function? More precisely, how is calculated the final trend component in this function? Thanks for your answer Myriam -- View this message in context: http://www.nabble.com/Decompose-function-%3A-calculation-of-each-component-tp24362207p24362207.html Sent from the R help mailing list archive at Nabble.com.

Dear all, I'm a bit stunned by the behaviour of a gam model using cyclic P-spline smoothers. I cannot provide the data, as I have about 61.000 observations from a time series. I use the following model : testgam <- gam(NO~s(x)+s(y,bs="cs")+s(DD,bs="cs")+s(TT),data=Final) The problem lies with the cyclic smoother I use for seasonal trends. The variable Final$y is a

i have data in one file below like & (i have such type of file =200,each file have below type of data) >t -0.15264004 0.056076439 -0.07276116 -0.00917326 -0.02069089 -0.00416232 -0.07225855 -0.02654577 -0.06131410 -0.09380202 0.057414014 -0.05239976 0.014397612 0.016145161 -0.00670587 0.018696335 0.036943654 -0.02450233 0.031161705 0.006513503 -0.02892329 -0.00831519 -0.00877744

Hi R users, I am developing two packages. Each package uses some functions from the other package. Now when I define these dependencies in the NAMESPACE file (via importFrom(XXXX,function1,....)), i get this error (when building one package): cyclic namespace dependency detected when loading 'XXXXXX', already loading ?YYYYYYY?, ?XXXXXXXXX? Is there any way to prevent this error?

Hi all, I would like to reference a resource twice, with different configurations. At the moment I do this: service { "service1": ensure => running, enable => true, require => Exec["some stuff"] } exec { "some stuff": command => "/etc/init.d/service1 stop; do some stuff required for service1", unless => "find out if already

Hello, I'm facing some problems while building LLVM 2.8 shared libraries from source using CMake: cmake -DBUILD_SHARED_LIBS=true .. This is the output error: CMake Error: The inter-target dependency graph contains the following strongly connected component (cycle): "LLVMARMCodeGen" of type SHARED_LIBRARY depends on "LLVMARMAsmPrinter"

I'm having trouble installing my quantreg package on R version 2.15.1 (2012-06-22) -- "Roasted Marshmallows" Copyright (C) 2012 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit) Seems odd since the CRAN version seems to be fine, but I'm seeing after compiling of the i386 and x86-64 versions and installing the

--- Pavel Øezníèek <pavel.reznicek@wo.cz> wrote: > I have made some steps and it helped me a bit: Wine > already does run! I'm glad for you! Closing the bug. > The most important thing is that I have configured > Wine to run with a fake > partition. > > But there are a few more problems left. > > 1) What's the reason that under KDE 2.0.0 & 2.0.1

Hi All, I'm trying to build klibc against my own kernel source tree. The build goes fine, the problem is to install it. As usr/klibc/README asks, I've create a symlink called linux pointing to my kernel tree: lrwxrwxrwx 1 root root 25 Jul 2 16:18 linux -> /usr/src/linux-2.6.22-rc6 anderson-herzer:/usr/local/src/klibc-1.5# export LANG=C anderson-herzer:/usr/local/src/klibc-1.5#

This patch allows one to repeat the '-x' option a third time to stop rsync from traversing potentially cyclic bind mounts that are on the same filesystem. For example, the following scenario would cyclically traverse the bind mounts until the OS (Linux in this case) hits a maximum traversal count, thank goodness. Other OSes may traverse the bind mount indefinitely... su cd mkdir

Dear all, I am encountering a cyclic dependency error when running R CMD check on an R package I wrote (R version 2.6.1, Mac OS X 10.4), see the error message below. Creating a new generic function for "print" in "clValid" Creating a new generic function for "summary" in "clValid" Creating a new generic function for "plot" in

Hi. I have to forecast a time series of a Internet network traffic bitrate. The data are in file http://www.forumaltavilla.it/joomla/datitesi/dati.datand the sampling time is every 0.05 seconds. Now, i want to use HoltWinters forecasting. This is my script. dt=1.58443823e-9 #0.05 seconds in years dati.ts=ts(scan("dati.dat"),start=0,deltat=dt) model=HoltWinters(dati.ts)

Okay, I tried installing OpenOffice beta, and I think I messed it up, so I wanted to uninstall it. I thought wilcards worked, so I tried: [root at localhost program]# rpm -e openoffice* error: package openoffice* is not installed Okay, so I couldn't figure out how to remove a bunch of RPM packages at once, so I did this: [root at localhost program]# rpm -qa | grep openoffice And

every time i try to run HoltWinters i get this error message: > HoltWinters(z, seasonal="additive") Error in decompose(ts(x[1:wind], start = start(x), frequency = f), seasonal) : time series has no or less than 3 periods what's going on? somebody please help me. -- View this message in context:

Hi, I would consider the calculation of r-squared in the following to be a bug, but then, I've been wrong before. It seems that R looks to see if the model contains an intercept term, and if it does not, computes r-squared in a way I don't understand. To my mind, the following are two alternative parametrizations of the same model, and should yield the same r-squared. Any insight much

Dear Knowledgeable R Community Members, Please excuse my ignorance, I apologize in advance if this is an easy question, but I am a bit stumped and could use a little guidance. I have a finite mixture modeling problem -- for example, a 2-component gaussian mixture -- where the components have a large overlap, and I am trying to use the "mclust" package to solve this problem. I need

Dear list members I want to analyze separately the months of a time series. In other words, I want to plot and fit models for each month separately. Taking the example of http://a-little-book-of-r-for-time-series.readthedocs.org/en/latest/src/timeseries.html births <- scan("http://robjhyndman.com/tsdldata/data/nybirths.dat") birthstimeseries <- ts(births, frequency=12,