Update from CAC-2008

Greetings from Montpellier, where Jeremy and I are attending CAC-2008. We’re now into our third day of the conference, and it has gotten off to a good start. I thought I’d just take a minute and highlight several talks that I really enjoyed.

Brynn Hibbert presented “Analysis of variance of complex data sets using GEMANOVA: An example using kill kinetics data.” GEMANOVA is essentially a variant of PARAFAC, used like ANOVA to determine what effects are significant, but in multi-way data. The talk made me want to make sure that we can get PARAFAC working in this way for our users. The trick is in setting the constraint options, and in automating the building of sequences of models with different constraints. In any case, this talk demonstrates that PARAFAC, in the right hands, is a very powerful and versatile technique.

“New proposals for PCA model building with missing data” was delivered by Alberto Ferrer. As usual, Alberto gave a very clear presentation–a nice talk to listen to. Alberto showed how methods for imputing missing data in PCA models when a model exists can also be used to develop new PCA models in the face of missing data. PLS_Toolbox, incidentally, uses one of these methods. It was also shown that the NIPALS method for building models with missing data does not work well in comparison to the other methods.

I also really enjoyed Henri Tapp’s talk, “OPLS: an ideal tool for interpreting PLS regression models?” Henri discussed, why, in his opinion, there really isn’t much advantage to OPLS, even in interpretability. (It is admitted by its creator, Johan Trygg, that it does not improve predictive ability over conventional PLS.) Another interesting point in Tapp’s talk was the bibliographic survey of papers citing the original OPLS paper, which showed that OPLS is mostly referenced by Umeå/Umetrics authors and Imperial University. I wonder, how much do you suppose the patent on OPLS has to do with this rather in-bred distribution?

My own talk, “Tools for Multivariate Calibration Robustness Testing with Observations on Effects of Data Preprocessing” was reasonably well-received (at least I wasn’t booed off the stage) and sparked some discussion. I’ve learned over the years that a relatively simple talk with some nice graphics is a good thing to present in the right after lunch spot, when conferees are suffering from PLS (post-lunch syndrome). And of course always energetic & enthusiastic Jeremy did a great job with “Automatic Sample Weighting for Inferential Modeling of Historical In-Control Process Data.”

So far, so good. More later!

BMW