similar to: Help on Time series seasonal Models in R package

Hi there, I am using the "ts" class of the "R" package. I have a data file containing a time series of 1152 entries. It is actually 4 days data cascaded together where the time interval of data collected is 5 minutes. Thus, I have 288 values per day. When I am trying to fit this data using a period of 288 with a seasonal model, using the arima(...) function, I am

Hello, I am new and am having a hard time getting the proper syntax for output from loops. I am working on a simulation to generate a null expectation of bee behavior. Pieces of it work. The part that I am having specific difficulty is in output of a vector from within the while loop that I am using. Basically the simulation works as such: I have a starting point and a neighbor matrix and a

Hi all, I would like to adjust the monthplot() of an stl() so that for a time-series with freq=12 (months): a) the curve on the panel for the k-th month graphs the seasonal values minus their monthly mean values b) add to the fig. the values of the k-th month of the seasonal + remainder, also minus their monthly mean values which corresponds to the 'seasonal diagnostic plot as described by

Hello, I am new to usin R - which is a great tool - and would like to know if R has a seasonal adjustment program for time series and/if it incorporates the Census Bureau's ARIMA x-12 seasonal adjustment program in any way? Thanks so much! Tony [[alternative HTML version deleted]]

Is there an R package that can model time series with multiple seasonal cycles, e.g., 7 wkdy x 24 hr , I have tried searching the Help, but have been unable to find anything. Any help would be appreciated. thank you, Spencer [[alternative HTML version deleted]]

To whom it may concern: I am trying to better understand the functionality of 'R' when making arima predictions to avoid any "Black Box" disadvantages. I'm fitting a seasonal arima model using the following command (having already loaded 'stat' package). arimaSeason <- arima(Data,order=c(1,0,1),seasonal=list(order=c(1,0,1),period=12)) I can then generate

Guys: Is it possible to simulate a seasonal ARIMA model in R? Which package can do this job? saji from Shanghai

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, I just couldn't find a R function which can fit multiple seasonal patters... i.e. in the following code: *arima(x = data, order = c(p, d, q), seasonal = list(order = c(P, D, Q), period = S), ... *** * there can be only one "period", am I right? What if the data seem to have three different seasonality cycles, 5, 12, 21? Thanks a lot! * [[alternative HTML version

Dear R-users, tsboot fails when I try to perform a block bootstrap on seaKen (package wq): these commands: require(wq) require(datasets) boot.block.sen <- function(data){seaKen(data)[[1]]} tsboot(sunspot.month, boot.block.sen, R=1999, l=12, sim="fixed") return: Error in seaKen(data) : x must be a 'ts' Any suggestion on how might I change seaKen in order to use it with

Hi R, Seems like the maximum seasonal 'q' parameter for the ?arima is 350. Any way, where we can increase this? Since I am working on 3 year (q=252*3) and 5 year(q=252*5) returns, I may require this option. Thanks. > fit=arima(r,c(3,0,0),seasonal = list(order = c(0, 0, 500), period = NA));tsdiag(fit);fit$aic Error in makeARIMA(trarma[[1L]], trarma[[2L]], Delta, kappa) :

Hi, Are there any R packages around which would break down a time series into a MxN table for analysis purposes? For example, show the total sales per month per calendar year. Jan Feb..... Total 2008 2009 Total Thanks, Eduard -- View this message in context: http://www.nabble.com/Seasonal-analysis-tp24844839p24844839.html Sent from the R help mailing list archive at Nabble.com.

Hi all, Does anyone know how ts objects ts(base) can be used within the 'seas' package? I would like to obtain seasonal statistics of regular time-series and for example look at the result of the plot.seas.var() function or use the change function() to look at change between periods or time-series. The nottem time-series are similar to the time-series we are analyzing (but with

Hi all, I am trying to analyse a time series data and want to make trend-season decomposition using STL approach in R. However I found the decomposition result seems to be sensitive to data points even with the robust option. More specifically, suppose I have a few years of monthly data. Using stl, I got a decomposition T1 + S1 + R1. Then I deleted the most recent two or three data points, the

Dear R list, I have a sequence of weekly observations of number of adults and larvae in various size classes from a butterfly population living in a subtropical area with pronounced wet and dry seasons. Wet and dry seasons are each defined 26 weeks long with fixed start and end dates. The data span 103 weeks (two seasons each of wet and dry) with some missing weeks. What I would like to do is

Hello, does anyone know about: a) simulating seasonal ARIMA models? arima out of package ts can fit it, but it does not look like it can simulates data from seasonal models b) fitting and simulating fractional seasonal ARIMA models? Hints will be appreciated, Henning -- Henning Rust Potsdam Institute for Climate Impact Research Dept. Integrated Systems Analysis Tel.: #49/331/288-2596

hallo to all I've to calculate an arima model and I need only the first and 365 th parameter and also the sar1 and the intercept, so I'm traing with: arima(X,order=c(365,0,0),seasonal=list(order=c(1,0,0),..),fixed=c(NA,rep(0,363),NA,NA,NA),transform.pars=F) but the error answer is: Error in polyroot(z) : polynomial degree too high (49 max) also there are problems in allocating memory

The following command crashes my Mac OS X version of R: (I'm running R on a PowerMac G5, with 1 GB of RAM and dual processors.) > arima.0 <- arima(w3.ts,order=c(1,0,0),seasonal=list(order=c (1,0,0),period=365)) -David Here is some background: w3.ts is hourly temperature data with about 20% NA's. It contains about 3.5 years of data. I am using period = 365, which makes

Are any seasonal adjustment programs, like Tramo/Seats, Census X12 ARIMA or Berliner Verfahren implemented in R? I am doing a simulation study and I don't know how to adjust the series in R. The possibility to access external the exe.files of the seasonal adjustment programs seems to be quite difficult. Can anyone help me? Thanks, Ingo

Hello All, I trying to find some way to fill in missing values in a seasonal time series. All the function that I find until now, don't have any reference to seasonal data and the output is very different of what I looking for. I also searched the forum but this problem don't have many information or people asking. Could someone indicate some links or packages related to this question?