Archive for Italy

Monica di Sardegna [Perdera]

Posted in Statistics with tags , , , , , on May 20, 2018 by xi'an

snapshop di Padova

Posted in Kids, pictures, Running, Travel with tags , , , , , , , on May 12, 2018 by xi'an

snapshot from Venezia #3 [jatp]

Posted in Statistics with tags , , , , , , , on May 6, 2018 by xi'an

snapshot from Venezia [jatp]

Posted in Statistics with tags , , , , , , , on April 29, 2018 by xi'an

an endless summer of Bayesian conferences

Posted in Statistics with tags , , , , on April 17, 2018 by xi'an

Another Bayesian conference that could fit the schedule of a few remaining readers of this blog, despite the constant flow of proposals! The 2018 Rimini Bayesian Econometrics Workshop will take place in Rimini, on the Italian Adriatic Sea, on 14-15 June, 2018. With Mike West as the plenary speaker. I attended this conference a few years ago and quite enjoyed its relaxed atmosphere.

non-identifiability in Venezia

Posted in Books, pictures, Statistics, Travel, University life with tags , , , , , , , , , on November 2, 2016 by xi'an

Last Wednesday, I attended a seminar by T. Kitagawa at the economics seminar of the University Ca’ Foscari, in Venice, which was about (uncertain) identifiability and a sort of meta-Bayesian approach to the problem. Just to give an intuition about the setting, a toy example is a simultaneous equation model Ax=ξ, where x and ξ are two-dimensional vectors, ξ being a standard bivariate Normal noise. In that case, A is not completely identifiable. The argument in the talk (and the paper) is that the common Bayesian answer that sets a prior on the non-identifiable part (which is an orthogonal matrix in the current setting) is debatable as it impacts inference on the non-identifiable parts, even in the long run. Which seems fine from my viewpoint. The authors propose to instead consider the range of possible priors that are compatible with the set restrictions on the non-identifiable parts and to introduce a mixture between a regular prior on the whole parameter A and this collection of priors, which can be seen as a set-valued prior although this does not fit within the Bayesian framework in my opinion. Once this mixture is constructed, a formal posterior weight on the regular prior can be derived. As well as a range of posterior values for all quantities of interest. While this approach connects with imprecise probabilities à la Walley (?) and links with robust Bayesian studies of the 1980’s, I always have difficulties with the global setting of such models, which do not come under criticism while being inadequate. (Of course, there are many more things I do not understand in econometrics!)

Ponte Foscari [jatp]

Posted in pictures, Running, Travel, University life with tags , , , , , , , on October 29, 2016 by xi'an