Archive for Bayesian graphical model

Rashomon, plus 47 ronins, plus…

Posted in Books, Kids, pictures, Travel with tags , , , , , , , , , , , on January 26, 2020 by xi'an

Another chance encounter (on Amazon) led me to read a graphical novel entitled Rashōmon, by Victor Santos. Which uses the same short stories from Ryūnosuke Akutagawa as Akira Kurosawa in his superlative film, if not with the same intensity. (The very first sentences are inspired from the first pages of the book, though.) And in a second part builds upon the tale of the 47 rônins which I read last summer in Koyasan. Plus a possible appearance of Miyamato Mushashi, the great 17th Century swordsman (depicted in two wonderful novels by Eiji Yoshikawa). While this is historically impossible, since Rashōmon takes place in the 12th Century and the 47 rônins acted in 1702, the theme cementing the story is the presence of a detective named Heigo Kobayashi, who “solves” both crimes but is nonetheless outsmarted by the novel “femme fatale”… Without a clear explanation as to how she did it.

While I found the rendering rather entertaining, with an original if convoluted drawing style, I was rather disappointed at the simplistic and Westernised adaptation of the subtle stories into a detective story. Calling upon (anachronic) ninjas as if the historical setting per se was not exotic enough. And the oddly modified role of the main female character into an Hammet-like heroin kills the ambivalence that is central to both Akutagawa’s and Kurosawa’s versions.

advances in Bayesian modelling a Venezia

Posted in Statistics with tags , , , , , , , , , on July 4, 2018 by xi'an

impressions from EcoSta2017 [guest post]

Posted in pictures, Statistics, Travel, University life with tags , , , , , , , , , on July 6, 2017 by xi'an

[This is a guest post on the recent EcoSta2017 (Econometrics and Statistics) conference in Hong Kong, contributed by Chris Drovandi from QUT, Brisbane.]

There were (at least) two sessions on Bayesian Computation at the recent EcoSta (Econometrics and Statistics) 2017 conference in Hong Kong. Below is my review of them. My overall impression of the conference is that there were lots of interesting talks, albeit a lot in financial time series, not my area. Even so I managed to pick up a few ideas/concepts that could be useful in my research. One criticism I had was that there were too many sessions in parallel, which made choosing quite difficult and some sessions very poorly attended. Another criticism of many participants I spoke to was that the location of the conference was relatively far from the city area.

In the first session (chaired by Robert Kohn), Minh-Ngoc Tran spoke about this paper on Bayesian estimation of high-dimensional Copula models with mixed discrete/continuous margins. Copula models with all continuous margins are relatively easy to deal with, but when the margins are discrete or mixed there are issues with computing the likelihood. The main idea of the paper is to re-write the intractable likelihood as an integral over a hypercube of ≤J dimensions (where J is the number of variables), which can then be estimated unbiasedly (with variance reduction by using randomised quasi-MC numbers). The paper develops advanced (correlated) pseudo-marginal and variational Bayes methods for inference.

In the following talk, Chris Carter spoke about different types of pseudo-marginal methods, particle marginal Metropolis-Hastings and particle Gibbs for state space models. Chris suggests that a combination of these methods into a single algorithm can further improve mixing. Continue reading