similar to: A question on seasonal time series - R package

Hi there, I am a graduate student using "R" for time series modeling. I have a weeks data with 96 data per day. I am trying to use a seasonal model with period of 96 (the size of the total data is 480) to fit the data after deriving the order information from ACF and PACF plots. But, I am getting the following error message "Error in optim(init[mask] ...) : non-finite

Hello, I have daily wind speed data and need to fit seasonal ARIMA model, problem is that my period is 365. But when I use arima(...) function, with period 365, I?m getting error message: ?Error in makeARIMA(trarma[[1]], trarma[[2]], Delta, kappa) : maximum supported lag is 350?. Can someone help me with this problem? Thank you Sincerely yours, Laura Saltyte

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) :

I guess this is more r-devel than r-help. Note, I am just the messenger - I have no idea what the user is trying to model here. arima() crashes R (segfault) with Linux R-2.7.0, Solaris R-2.6.0: *** caught segfault *** address 42400000, cause 'memory not mapped' Traceback: 1: .Call(R_getQ0, phi, theta) 2: makeARIMA(trarma[[1]], trarma[[2]], Delta, kappa) 3: arima(x, c(1, 0, 1), c(1,

Hi, the function makeARIMA(), designed to construct some state space representation of an ARIMA model, uses a C function called getQ0, which can be found at the end of arima.c in R source files (library stats). getQ0 takes two arguments, phi and theta, and returns the covariance matrix of the state prediction error at time zero. The reference for getQ0 (cited by help(arima)) is:

Hi R-Experts, Currently I'm using an univariate time series in which I'm going to apply KalmanLike(),KalmanForecast (),KalmanSmooth(), KalmanRun(). For I use it before makeARIMA () but I don't understand and i don't know to include the seasonal coefficients. Can anyone help me citing a suitable example? Thanks in advance. ------------------------------------------

Thanks a lot to everybody that helped me out with this. Conclusions: (1) In order to edit arima in R: >fix(arima) or alternatively: >arima<-edit(arima) (2) This is not contained in the "Introduction to R" manual. (3) A "productive" fix of arima is attached (arma coefficients printed out and error catched so that it doesn't halt parent loops to search for

Hello everyone, I was trying to fit an arima model to a daily historical data, but, for some reason, havent been able to. I basically have 212 observations (from 12/1/2012 to 06/30/2013) containing the number of transits for a particular vessel. The following messages are produced by R: dailytrans.fit<-arima(dailytrans$transits, order=c(0,1,2), seasonal=list(order=c(0,1,2), period=365),

I've rolled up R-1.9.1.tgz a short while ago. This is a maintenance version mainly to fix a number of minor bugs and issues (the most annoying one seems to have been the change to barplots of tables) and some installation issues. Because of the relocation the CVS archives, there is no direct access to the files until they show up on the CRAN master site. You can then get it from

I've rolled up R-1.9.1.tgz a short while ago. This is a maintenance version mainly to fix a number of minor bugs and issues (the most annoying one seems to have been the change to barplots of tables) and some installation issues. Because of the relocation the CVS archives, there is no direct access to the files until they show up on the CRAN master site. You can then get it from

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, 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