similar to: Question about fitting seasonal ARIMA in R?

Hello R People: When using the arima function with the seasonal option, are the seasonal options only good for monthly and quarterly data, please? Also, I believe that weekly and daily data are not appropriate for seasonal parm estimation via arima. Is that correct, please? Thanks, Sincerely, Laura Holt mailto: lauraholt_983 at hotmail.com download!

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

I'm trying to use the following command. arima (x, order = c(p,d,q), seasonal =list(order=c(P,D,Q), period=s) How can I write an estimated seasonal ARIMA model from the outputs. To be specifically, which sign to use? I know R uses a different signs from S plus. Is it correct that the model is: (1-ar1*B-ar2*B^2-...)(1-sar1*B^s-sar2*B^2s-....)(1-B)^d(1-B^s)^D

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),

Dear all, I stumbled upon what appears to be a troublesome issue when sampling from an ARIMA model (from Rob Hyndman's excellent 'forecast' package) that contains a seasonal AR component. Here's how to reproduce the issue. (I'm using R 2.9.2 with forecast 2.19; see sessionInfo() below). First some data: > x <- c( 0.132475, 0.143119, 0.108104, 0.247291, 0.029510,

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

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]]

I am using AUTO ARIMA for forecasting. But it is not detecting 'seasonality term' of its own for any data. Is there any other method by which we can detect seasonality and its frequency for any data? Is there any method through which seasonality and its frequency can be automatically detected from ACF plot? -- Siddharth Arun, 4th Year Undergraduate student Industrial Engineering and

> It might clarify your thinking to note that a seasonal ARIMA model > is just an ``ordinary'' ARIMA model with some coefficients > constrained to be 0 in an efficient way. E.g. a seasonal AR(1) s = > 4 model is the same as an ordinary (nonseasonal) AR(4) model with > coefficients theta_1, theta_2, and theta_3 constrained to be 0. You > can get the same answer as from

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

I am puzzled by the warning message in the output below. It appears whether or not I fit the seasonal term (but the precise point of doing this was to fit what is effectively a second seasonal term). Is there some deep reason why AR parameters ("Warning message: some AR parameters were fixed: ...") should somehow intrude into the fitting of a model that has only MA terms? >

Hi, I have the following code from Splus that I'd like to migrate to R. So far, the only problem is the arima.filt function. This function allows me to filter an existing time-series through a previously estimated arima model, and obtain the residuals for further use. Here's the Splus code: # x is the estimation time series, new.infl is a timeseries that contains new information # a.mle

Hello, I have a several time series, which I would like to check for their best fitted Arima model (I am checking for the lowest aic value). Which lets me raise two questions: 1) is there are more efficient way, than using 6 for-loops? 2) sometimes the system cannot calculate with given parameters - is there a more efficient solution than I found? I hope, you can help me to make this

Dear R community, I have a project with electricity load forecasting, and I got hourly data for system load. If you haven't worked with electricity before, seasonality comes in many flavors: a daily pattern, with a peak at around 7pm; a weekly pattern, in which we use more electricity on weekdays in comparison to weekends; a winter-summer pattern, with air conditioning and heaters playing an

Good evening! I have a question regarding forecast package and time series analysis. My syntax: x<-c(253, 252, 275, 275, 272, 254, 272, 252, 249, 300, 244, 258, 255, 285, 301, 278, 279, 304, 275, 276, 313, 292, 302, 322, 281, 298, 305, 295, 286, 327, 286, 270, 289, 293, 287, 267, 267, 288, 304, 273, 264, 254, 263, 265, 278) library(forecast) arima(x, order=c(1,1,2),

Colleagues I am a new to R but already love it. I have the following problem: I fitted arima model to my time series like this (please ignore modeling parameters as they are not important now): x = scan("C:/data.txt") x = ts(x, start=1, frequency=1) x.fit<-arima(x, order = c(1,0,0), seasonal = list(order=c(0,0,1))) Now I want to use this model for forecasting and backtesting (!).

I am using auto.arima() for forecasting.When I am using any in built data such as "AirPassangers" it is capturing seasonality. But, If I am entering data in any other format(in vector form or from an excel sheet) it is not detecting seasonality. Is there any specific format in which it detects seasonality or I am doing some thing wrong? Does data have to be entered in a specific

Hi people, I´m trying to development a simple routine to run many Arima models result from some parâmeters combination. My data test have one year and daily level. A part of routine is: for ( d in 0:1 ) { for ( p in 0:3 ) { for ( q in 0:3 ) { for ( sd in 0:1 ) { for ( sp in 0:3 ) { for ( sq in 0:3 ) {

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

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