Analytics 2011 Conference

From http://www.sas.com/events/analytics/us/

The Analytics 2011 Conference Series combines the power of SAS’s M2010 Data Mining Conference and F2010 Business Forecasting Conference into one conference covering the latest trends and techniques in the field of analytics. Analytics 2011 Conference Series brings the brightest minds in the field of analytics together with hundreds of analytics practitioners. Join us as these leading conferences change names and locations. At Analytics 2011, you’ll learn through a series of case studies, technical presentations and hands-on training. If you are in the field of analytics, this is one conference you can’t afford to miss.

Conference Details

October 24-25, 2011
Grande Lakes Resort
Orlando, FL

Analytics 2011 topic areas include:

Doing Time Series using a R GUI

The Xerox Star Workstation introduced the firs...
Image via Wikipedia

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

 

> bulkfit(AirPassengers$x)
$res
ar d ma      AIC
[1,]  0 0  0 1790.368
[2,]  0 0  1 1618.863
[3,]  0 0  2 1522.122
[4,]  0 1  0 1413.909
[5,]  0 1  1 1397.258
[6,]  0 1  2 1397.093
[7,]  0 2  0 1450.596
[8,]  0 2  1 1411.368
[9,]  0 2  2 1394.373
[10,]  1 0  0 1428.179
[11,]  1 0  1 1409.748
[12,]  1 0  2 1411.050
[13,]  1 1  0 1401.853
[14,]  1 1  1 1394.683
[15,]  1 1  2 1385.497
[16,]  1 2  0 1447.028
[17,]  1 2  1 1398.929
[18,]  1 2  2 1391.910
[19,]  2 0  0 1413.639
[20,]  2 0  1 1408.249
[21,]  2 0  2 1408.343
[22,]  2 1  0 1396.588
[23,]  2 1  1 1378.338
[24,]  2 1  2 1387.409
[25,]  2 2  0 1440.078
[26,]  2 2  1 1393.882
[27,]  2 2  2 1392.659
$min
ar        d       ma      AIC
2.000    1.000    1.000 1378.338
> ArimaModel.5 <- Arima(AirPassengers$x,order=c(0,1,1),
+ include.mean=1,
+   seasonal=list(order=c(0,1,1),period=12))
> ArimaModel.5
Series: AirPassengers$x
ARIMA(0,1,1)(0,1,1)[12]
Call: Arima(x = AirPassengers$x, order = c(0, 1, 1), seasonal = list(order = c(0,      1, 1), period = 12), include.mean = 1)
Coefficients:
ma1     sma1
-0.3087  -0.1074
s.e.   0.0890   0.0828
sigma^2 estimated as 135.4:  log likelihood = -507.5
AIC = 1021   AICc = 1021.19   BIC = 1029.63
> summary(ArimaModel.5, cor=FALSE)
Series: AirPassengers$x
ARIMA(0,1,1)(0,1,1)[12]
Call: Arima(x = AirPassengers$x, order = c(0, 1, 1), seasonal = list(order = c(0,      1, 1), period = 12), include.mean = 1)
Coefficients:
ma1     sma1
-0.3087  -0.1074
s.e.   0.0890   0.0828
sigma^2 estimated as 135.4:  log likelihood = -507.5
AIC = 1021   AICc = 1021.19   BIC = 1029.63
In-sample error measures:
ME        RMSE         MAE         MPE        MAPE        MASE
0.32355285 11.09952005  8.16242469  0.04409006  2.89713514  0.31563730
Dataset79 <- predar3(ArimaModel.5,fore1=5)

 

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