Auto.arima vs autobox do they differ?

From reading posts on this site I know there is an R function auto.arima (in the forecast package). I also know that IrishStat, a member of of this site built the commercial package autobox in the early 1980s. As these two packages exist today and automatically select arima models for given data sets what do they do differently? Will they possibly produce different models for the same data set?



AUTOBOX would definitely deliver/identify a different model if one or more of the following conditions is met

1) there are pulses in the data

2) there is 1 or more level/step shift in the data

3) if there are seasonal pulses in the data

4) there are 1 or more local time trends in the data that are not simply remedied

5) if the parameters of the model change over time

6) if the variance of the errors change over time and no power transformation is adequate.

In terms of a specific example, I would suggest that both of you select/make a time series and post both of them to the web. I will use AUTOBOX to analyse the data in an unattended mode and I will post the models to the list. You then run the R program and then each of you make a separate objective analysis of both results, pointing out similarities and differences. Send those two models complete with all available supporting material including the final error terms to me for my comments. Summarize and presents these results to the list and then ask readers of the list to VOTE for which procedure seems best to them.

Source : Link , Question Author : Michael R. Chernick , Answer Author : Nick Cox

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