sunset on the Krkonošská magistrála [#2]

sunset on the Krkonošská magistrála

further up North

impression, soleil couchant

 

As the sunset the day before had been magnificent [thanks to the current air pollution!], I attempted to catch it from a nice spot and went to the top of the nearby hill. The particles were alas (!) not so numerous that evening and so I only got this standard view of the sun going down. Incidentally, I had read a few days earlier in the plane from Vienna that the time and date when Monet’s Impression, Soleil Levant was painted had been identified by a U.S. astronomer as 7h35 on the 13th of Novembre 1872. In Le Havre, Normandy. An exhibit in the nearby Musée Marmottan retraces this quest…

future of computational statistics

I am currently preparing a survey paper on the present state of computational statistics, reflecting on the massive evolution of the field since my early Monte Carlo simulations on an Apple //e, which would take a few days to return a curve of approximate expected squared error losses… It seems to me that MCMC is attracting more attention nowadays than in the past decade, both because of methodological advances linked with better theoretical tools, as for instance in the handling of stochastic processes, and because of new forays in accelerated computing via parallel and cloud computing, The breadth and quality of talks at MCMski IV is testimony to this. A second trend that is not unrelated to the first one is the development of new and the rehabilitation of older techniques to handle complex models by approximations, witness ABC, Expectation-Propagation, variational Bayes, &tc. With a corollary being an healthy questioning of the models themselves. As illustrated for instance in Chris Holmes’ talk last week. While those simplifications are inevitable when faced with hardly imaginable levels of complexity, I still remain confident about the “inevitability” of turning statistics into an “optimize+penalize” tunnel vision…  A third characteristic is the emergence of new languages and meta-languages intended to handle complexity both of problems and of solutions towards a wider audience of users. STAN obviously comes to mind. And JAGS. But it may be that another scale of language is now required…

If you have any suggestion of novel directions in computational statistics or instead of dead ends, I would be most interested in hearing them! So please do comment or send emails to my gmail address bayesianstatistics…

métro static

“Mon premier marathon je le fais en courant.” [I will do my first marathon running.]

a week at the lake (#4)