This Monday, I made a most pleasant trip to the Observatoire de Paris, which campus is located in Meudon and no longer in Paris. (There also is an Observatoire de Paris campus in downtown Paris, created in 1667, where no observation can take place.) Most pleasant for many reasons. First, I was to meet with Frédéric Arenou and two visiting astrostatisticians from Kolkata, India, whom I met in Bangalore two years ago. Working on a neat if no simple issue of inverted mean estimation. Second, because the place is beautiful, with great views of Paris (since the Observatoire is on a ridge), and with a classical-looking building actually made of recycled castle parts after the Franco-Prussian war of 1870, and because Frédéric gave us a grand tour of place. And third, because I went there by bike through the Forêt de Meudon which I did not suspect was that close to home and which I crossed on downhill muddy trails that made me feel far away from Paris! And giving me the opportunity to test the mettle of a new mountain bike elsewhere than again Parisian SUVs. (This was the first day of a relatively intense biking week, which really helped with the half-marathon training: San Francisco ½ is in less than a month!!! And I am in wave 2!)
Archive for Bangalore
While in Bangalore, I spotted Richard Dawkins’ The God delusion in the [fantastic if chaotic] campus bookstore and bought the Indian edition for a nominal amount. I read most of it during my week in Boston. And finished by the lake in Maine. While I agree with most of the points made in Dawkins’ book about the irrationality of religions, and of their overall negative impact on human societies, I found the first part rather boring in that I see little appeal in dissecting so minutely the [infinitely many] incoherences of religious myths and beliefs, as this will likely miss the intended target [i.e., literal believers]. Similarly, the chapter on evolution versus intelligent design made valuable points, albeit I had already seen them before. Nothing wrong with repeating those, in particular that evolution has little to do with chance, but again unlikely to convince the [fundamentalist] masses. Overall, the book mostly focus on the Judeo-Christian-Muslim branch of religions, which may reflect on the author’s own culture and upbringing but also misses the recent attempts of Buddhism to incorporate science into their picture.
“A universe in which we are alone except for other slowly evolved intelligences is a very different universe from one with an original guiding agent whose intelligent design is responsible for its very existence.” (p.85)
What is most interesting in the book (for me) is when Dawkins tries to set the God hypothesis as a scientific hypothesis and to apply scientific methods to validate or invalidate this hypothesis. Even though there is no p-value or quantitative answer at the end. Despite the highly frequent use of “statistical” and “statistically improbable” in the corresponding chapter. What’s even more fascinating is Dawkins’ take at Bayesian arguments! Either because it is associated with a reverent or because it relies on subjective prior assessments, Bayesian statistics does not fit as a proper approach. Funny enough, Dawkins himself relies on subjective prior probabilities when discussing the likelihood of find a planet such as Earth. Now, into the details [with the Devil1] in a rather haphazard order or lack thereof: Continue reading
On the last day of the IFCAM workshop in Bangalore, Marc Lavielle from INRIA presented a talk on mixed effects where he illustrated his original computer language Monolix. And mentioned that his CRC Press book on Mixed Effects Models for the Population Approach was out! (Appropriately listed as out on a 14th of July on amazon!) He actually demonstrated the abilities of Monolix live and on diabets data provided by an earlier speaker from Kolkata, which was a perfect way to start initiating a collaboration! Nice cover (which is all I saw from the book at this stage!) that maybe will induce candidates to write a review for CHANCE. Estimation of those mixed effect models relies on stochastic EM algorithms developed by Marc Lavielle and Éric Moulines in the 90’s, as well as MCMC methods.
As I am now back home after a rather lengthy and somewhat eventful trip [getting too early to Bangalore airport with 3 hours to spend in the nice and very quiet lounge, followed by another 5 hour wait in the very nice but no so quiet Bombay airport lounge, no visit to the cockpit this time!, and then the usual sick passenger blocking all trains from Paris-Charles de Gaulle airport for one hour, reaching home to find my 97-year old neighbour fallen in her kitchen and calling for help!], I cannot but reflect on the difference between my two trips to India, from the chaos of Varanasi to the orderly peace of the campus of the Indian Institute of Science of Bangalore and even to some extent of the whole city of Bangalore, all proportions guarded. Even managing to get a [new] pair of [new] prescription glasses (or rather spectacles) within three days!
I thus found this trip much less stressful and much profitable, from enjoying the local food to discussing with Indian statisticians. The purpose of the IFCAM workshop was to bring both groups together for potential joint projects funded by IFCAM (at the travel level). While I found most talks were driven by specific applications, esp. in genomics, there are directions where we could indeed collaborate, from capture-recapture to astrostatistics. So it may be that I’ll be back in India in a near future!