**A**s I glanced thru the recent arXiv postings in statistics, I found an overload of potential goodies, many more than I could handle in a reasonable time (unless I give up the NYT altogether!)…

**F**or instance, Paulo Marques—a regular ‘Og commenter—wrote about an extension of Chib’s formula when the posterior is approximated in a non-parametric manner. (*This was an idea I had toyed with at a time without pursuing it anywhere…)* I wonder at the stability of the approximation for two reasons: (i) Chib’s or Bayes’ formula does not require an expectation as the ratio is constant in θ; averaging over realisations of θ could have negative effects on the stability of the approximation (or not); (ii) using a non-parametric estimate will see the performances of Chib’s approximation plummet as the dimension of θ increases, most likely.

**A**nother post is by Nogales, Pérez, and Monfort and deals with a Monte Carlo formula for conditional expectations that leaves me quite puzzled… More than excited about a potential application in ABC. Indeed, the idea is to replace the conditioning on the (hard) equality with a soft ball around the equality with a tolerance level ε. Since the authors do not seem particularly interested in ABC, I do no see the point in this technique. The first example they present does not account for the increasing computational effort as ε decreases. The second part of the paper deals with the best invariant estimator of the position parameter of a general half-normal distribution, using two conditional expectations in Proposition 2. I wonder how the method compares with bridge sampling and MCMC methods. As the paper seems to have gone beyond the Monte Carlo issue at this stage. And focus on this best invariant estimation…

**T**hen Feroz, Hobson, Cameron and Pettitt posted a work on importance nested sampling, on which I need to spend more time given the connection to our nested sampling paper with Nicolas. The paper builds on the Multinest software developped by Feroz, Hobson and co-authors. *(Whose above picture is borrowed from.)*

**A** side post on the moments of the partial non-central chi-square distribution function by Gill, Segura and Temme, since I always liked the specifics of this distribution… No comments so far!

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