At the end of august 2013, I was lucky enough to attend the *Rencontres des jeunes statisticiens* (young statisticians meeting). It is organised every other year by the *Société Française de Statistique* (French Statistical Society). It was thrilling to meet all these fellow statisticians in the making!

A lot of the talks were very interesting. In particular, one made me think of a recent post from Roger Peng on the famous Simply Statistics blog. Benjamin Guedj developed a nonlinear aggregation strategy, an approach aggregating different solutions (from different modeling) to a regression problem. It is implemented as an R package, COBRA, and it seems to performs quite good (and fast). Even though I suspect it might choke a little on difficult datasets (n<<p anyone?), I find it quite clever. And, relating to R. Peng post, it has the advantage of reducing the “researcher degrees of freedom”. Could it be a first step towards a deterministic statistical machine?

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