Until recently I had been thinking that RKWard was the only R GUI supporting Time Series Models-
however Bob Muenchen of http://www.r4stats.com/ was helpful to point out that the Epack Plugin provides time series functionality to R Commander.
Note the GUI helps explore various time series functionality.
Using Bulkfit you can fit various ARMA models to dataset and choose based on minimum AIC
And I also found an interesting Ref Sheet for Time Series functions in R-
http://cran.r-project.org/doc/contrib/Ricci-refcard-ts.pdf
and a slightly more exhaustive time series ref card
http://www.statistische-woche-nuernberg-2010.org/lehre/bachelor/datenanalyse/Refcard3.pdf
Also of interest a matter of opinion on issues in Time Series Analysis in R at
http://www.stat.pitt.edu/stoffer/tsa2/Rissues.htm
Of course , if I was the sales manager for SAS ETS I would be worried given the increasing capabilities in Time Series in R. But then again some deficiencies in R GUI for Time Series-
1) Layout is not very elegant
2) Not enough documented help (atleast for the Epack GUI- and no integrated help ACROSS packages-)
3) Graphical capabilties need more help documentation to interpret the output (especially in ACF and PACF plots)
More resources on Time Series using R.
http://people.bath.ac.uk/masgs/time%20series/TimeSeriesR2004.pdf
and http://www.statoek.wiso.uni-goettingen.de/veranstaltungen/zeitreihen/sommer03/ts_r_intro.pdf
and books
http://www.springer.com/economics/econometrics/book/978-0-387-77316-2
http://www.springer.com/statistics/statistical+theory+and+methods/book/978-0-387-75960-9
http://www.springer.com/statistics/statistical+theory+and+methods/book/978-0-387-75958-6
http://www.springer.com/statistics/statistical+theory+and+methods/book/978-0-387-75966-1
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Yes, R is gaining in functionality no doubt, but……
Like SAS, Oracle etc, it is not able to adequately model this time series.
I presented this at the IBF in April 2009. Take a look at slide 14 to 17 and you will see that R is not identifying the 3 pulses in the last year. If you are not accounting for outliers than you really aren’t modeling the data set like it needs to be. Additionally, if you aren’t accounting for level shifts, changes in seasonality or level shifts you are also in deep trouble.
I didn’t see a LOG being added to the R code above which I will give the poster kudos for!
Click to access vegas_ibf_09a.pdf
there is no point in adding log transforms just for the heck of it! I would be interested in knowing more on autobox capabilities and integration with other software
Thanks for the useful info. Will be watching this space for further improvements in R’s support of time series.