Xi'an's Og

We have just arXived our paper on insufficient Gibbs sampling with Antoine Luciano and Robin Ryder, from Université Paris Dauphine. This is Antoine’s first paper and part of his PhD. (In particular, he wrote the entire code.) The idea stemmed from a discussion on ABC benchmarks, like the one when the pair (median, MAD) is the only available observation. With no available joint density, the setting seems to prohibit calling for an MCMC sampler. However, simulating the complete data set conditional on these statistics proves feasible, with a bit of bookkeeping. With obviously much better results [demonstrated above for a Cauchy example] than when calling ABC and at a very similar cost. (If not accounting for the ability of ABC to be parallelised.)  The idea can be extended to other settings, obviously, as long as completion remains achievable. (And a big thanks to our friend Ed George who suggested the title, while at CIRM. I had suggested “Gibbs for boars” as a poster title, in connection with the historical time-line of

Gibbs for Kids (Casella and George) — Gibbs for Pigs (Gianola) — Gibbs for Robust Pigs = Gibbs for Boars

and the abundance of boars on the Luminy campus, but this did not sound convincing enough for Antoine.)

This entry was posted on July 29, 2023 at 12:23 am and is filed under Books, Kids, Statistics, University life with tags ABC, arXiv, boar, CIRM, George Casella, Gibbs sampling, insufficiency, latent variable, Luminy campus, mad, median, PhD thesis, poster session, Université Paris Dauphine. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.