advancements in Bayesian methods and implementations

The handbook of (recent) advances in Bayesian methods is now out (at the Elsevierian price of $250!) with chapters on Gibbs posteriors [Ryan Martin & Nicolas Syring], martingale distributions [Walker], selective inference [Daniel García Racines & Alastair Young], manifold simulations [Sumio Watanabe], MCMC for GLMMs [Vivek Roy] and multiple testing [Noirrit Chandra and Sourabh Bhattacharya]. (Along with my chapter on 50 shades of Bayesian testing.) Celebrating 102 years for C.R. Rao, one of the three editors of this volume (as well as the series) along with Arni Srivastava Rao and Alastair Young.

Advancements in Bayesian Methods and Implementations [to appear]

As noted in another post, I wrote a chapter on Bayesian testing for an incoming handbook, Advancements in Bayesian methods and implementations which is published by Elsevier at an atrocious price (as usual). Here is the table of contents:

1. Fisher Information, Cramèr-Rao and Bayesian Paradigm by Roy Frieden
2. Compound beta binomial distribution functions by Angelo Plastino
3. MCMC for GLMMS by Vivekananda Roy
4. Signal Processing and Bayesian by Chandra Murthy
5. Mathematical theory of Bayesian statistics where all models are wrong by Sumio Watanabe
6. Machine Learning and Bayesian by Jun Zhu
7. Non-parametric Bayes by Stephen Walker
8. [50 shades of] Bayesian testing [of hypotheses] by Christian P. Robert
9. Data Analysis with humans by Sumio Kaski
10. Bayesian Inference under selection by G. Alastair Young
10. Variational inference or Functional horseshoe by Anirban Bhattacharya
11. Generalized Bayes by Ryan Martin

and my chapter is also available on arXiv, quickly gathered from earlier short courses at O’Bayes meetings and some xianblog entries on the topic, hence not containing much novelty!

the many nuances of Bayesian testing [CERminar]