With 24 values you are asking the impossible from your data. If you use the standard Box Jenkins approach rather than an automatic ARIMA and using any prior knowledge of the data you might manage some form of forecast. Look at graphs of the data and their first differences. Look at graphs of the autocorrelation and partial autocorrelation functions. There are a range of text books that describe this kind of manual Box-Jenkins approach.
There is an excellent account of stationarity and related matters in Pfaff, B (2006), "Analysis of Integrated and Cointegrated Time Series with R", in the Springer USE R! series. This also contains an account of ARMA models. Best regards John On 26/11/2007, Ozcan Asilkan <[EMAIL PROTECTED]> wrote: > Hello, > > I am very new to R and Time Series. I need some help including R codes > about the following issues. I' ll really appreciate any number of > answers... > > # I have a time series data composed of 24 values: > myinput = c(n1,n2...,n24); > # In order to make a forecasting a, I use the following codes > result1 = arima(ts(myinput),order = c(p,d,q),seasonal = list(order=c(P,D,Q))) > result2 = forecast(result1,12) > plot(result2) > > Now, by using R code... > > 1) How can I determine if my data is statitonary or not ? (trend & > seasonal effects) > 2) If not, how can I make it stationary ? > 3) Is arima() function used only on STATIONARY data ? Or does it first > determine if the data is stationary or not and makes it stationary ? > (if it is non-stationary) > 4) I tried different parameter values in arima() function, but every > parameter gave very different results :(( . I > even found & tried best.arima() function but it also gave > unsatisfactory result. So, how can I calculate the optimum arima() > parameters (p,d,q,P,D,Q) that fit my data best ? > > Thanks in advance, best wishes.. > > Ozzy > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- John C Frain Trinity College Dublin Dublin 2 Ireland www.tcd.ie/Economics/staff/frainj/home.html mailto:[EMAIL PROTECTED] mailto:[EMAIL PROTECTED] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
