After ABC in Paris in 2009, ABC in London in 2011, and ABC in Roma last year, things are accelerating since there will be—as I just learned— an ABC in Sydney next July (not June as I originally typed, thanks Robin!). The workshop on the current developments of ABC methodology thus leaves Europe to go down-under and to take advantage of the IMS Meeting in Sydney on July 7-10, 2014. Hopefully, “ABC in…” will continue its tour of European capitals in 2015! To keep up with an unbroken sequence of free workshops, Scott Sisson has managed to find support so that attendance is free of charge (free as in “no registration fee at all”!) but you do need to register as space is limited. While I would love to visit UNSW and Sydney once again and attend the workshop, I will not, getting ready for Cancún and our ABC short course there.
Archive for Australia
Dirk Kroese (from UQ, Brisbane) and Joshua Chen (from ANU, Canberra) just published a book entitled Statistical Modeling and Computation, distributed by Springer-Verlag (I cannot tell which series it is part of from the cover or frontpages…) The book is intended mostly for an undergrad audience (or for graduate students with no probability or statistics background). Given that prerequisite, Statistical Modeling and Computation is fairly standard in that it recalls probability basics, the principles of statistical inference, and classical parametric models. In a third part, the authors cover “advanced models” like generalised linear models, time series and state-space models. The specificity of the book lies in the inclusion of simulation methods, in particular MCMC methods, and illustrations by Matlab code boxes. (Codes that are available on the companion website, along with R translations.) It thus has a lot in common with our Bayesian Essentials with R, meaning that I am not the most appropriate or least
unbiased reviewer for this book. Continue reading
Today, Ewan Cameron arXived a paper that generalises our Robert and Marin (2010) paper on the measure theoretic difficulties (or impossibilities) of the Savage-Dickey ratio and on the possible resolutions. (A paper of mine’s I like very much despite it having neither impact nor quotes, whatsoever! Until this paper.) I met Ewan last year when he was completing a PhD with Tony Pettitt at QUT in astrostatistics, but he
also worked did not work on this transdimensional ABC algorithm with application to worm invasion in Northern Alberta (arXive I reviewed last week)… Ewan also runs a blog called Another astrostatistics blog, full of goodies, incl. the one where he announces he moves to… zoology in Oxford! Anyway, this note extends our paper and a mathematically valid Savage-Dickey ratio representation to the case when the posterior distributions have no density against the Lebesgue measure. For instance for Dirichlet processes or Gaussian processes priors. Using generic Radon-Nykodim derivatives instead. The example is somewhat artificial, superimposing a Dirichlet process prior onto the Old faithful benchmark. But this is an interesting entry, worth mentioning, into the computation of Bayes factors. And the elusive nature of the Savage-Dickey ratio representation.
Just got this announcement that MaxEnt 2013, 33ième du genre, is taking place in Canberra, Australia, next December. (Which is winter here but summer there!) See the website for details, although they are not yet aplenty! I took part in MaxEnt 2009, in Oxford, Mississipi, but will not attend MaxEnt 2013 as it is (far away and) during O-Bayes 2013 in Duke…