I’ll be giving a talk at ANU on Tuesday, for the Canberra branch of the Statistical Society of Australia: “Statistics from Mars – Bayesian signal processing for Raman Spectroscopy.” I’ll also be presenting a talk at the 12th International Conference on Monte Carlo Methods and Applications (MCM 2019) at UTS. I’ve volunteered as the newsletter editor for the Bayes Section of SSA. Our June newsletter is now available online.

I’ve just released a new version of my R package serrsBayes. It includes a fix for a major bug, where I was using the upper-triangular instead of the lower-triangular Cholesky factor for random-walk Metropolis proposals. It also includes a reimplementation of fitVoigtPeaksSMC using RcppEigen with OpenMP for parallelism. This function is still slower than fitSpectraSMC, but should result in a big speed improvement if you have OpenMP multi-threading enabled. See the release notes and CRANberries for details.

A couple of seminars that I wanted to highlight in the next couple of weeks: one from A/Prof Mirko Draca (Department of Economics, University of Warwick) and another from me. Mirko will be speaking in the NIASRA Seminar Series this week at Wollongong, while I’ll be flying home to Brisbane next week to present a talk at the ACEMS Workshop on Intractable Likelihoods & ABC. Abstracts for both talks are below:

I was very lucky to be invited to attend a 5 day workshop at the Casa Matemática Oaxaca (CMO-BIRS), “Computational Statistics and Molecular Simulation: A Practical Cross-Fertilization” where I presented my work on the Rao-Blackwellized particle filter for Bayesian modelling of Raman spectroscopy. A link to the video is here and the abstract for my talk is below. See also commentary on selected talks by one of the organisers, Prof. Xi’an.

I’ve just arXiv’d another revision of my paper on the PFAB algorithm: arXiv:1503.08066v3 [stat.CO]. It includes a rather elegant proof of the exact mean and variance of the sufficient statistic S(y) in the hottest state, when the inverse temperature $\beta = 0$. The proof by my co-author Geoff Nicholls holds for any Potts model with first-order neighbours. That is, the nearest 4 neighbours in a 2D lattice (or 6 neighbours in 3D). For posterity, I present my rather clunkier proof below, which involves induction on dimension for a rectangular lattice.

It was great to be back in Brissie for the first time since my PhD graduation, 3 years ago. The R Consortium have made video of all of the talks available on YouTube – a link to mine is below, along with my slides.

As usual when I set up a new computer, I like to update the list of software that I have installed. This is particularly pertinent when I’m about to move back to Australia and will have to say goodbye to my beloved MacBook Air. Note that I won’t be running R using the Windows Subsystem for Linux, although this is definitely something I’m keen to experiment with at some point. Instead, I’ll be using MRO, since it includes the Intel Math Kernel Library (MKL) for Windows. This is important if you run R packages (including RcppArmadillo) that make heavy use of linear algebra.

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