I don’t fully understood what is meant with the term ‘model management’ when I entered this session, but it appeared to be quite an interesting session, although apparently, there are some widely different interpretations on what it actually means.
With increased computer power, it has become very easy to estimate models. It has even become so easy, that we easily estimate loads of models, resulting in the piling up of lots of data. The managing of large sets of models by hand can be cumbersome work, as was stated by Ralf Seger. He presented MORET – A software for model management. MORET collects all input from R, and stores the data, corresponding input and models in a database. The software then allows the comparison of global model characteristics. It is even possible to manually define what elements of information needs to be extracted from what types of models!
After models have been stored in MORET, they can be accessed from within R-Project, or they can be ‘dragged’ from within the MORET interface. So, basically, you can retrieve the full history of all the analysis you’ve done in a long period, or even career! Check it out on: www.rosuda.org
In a very different meaning of model management, Werner Stahel presented an augmented version of a regression function (”Yet another Regression Function”). It primarily has a different way of doing residual analysis and improves the way anova tables are calculated from regression objects. At times, he moves away form what is customary in regression analysis, so I wonder how many people will use it, or especially report the new measures in their publications.