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.

I’ll be attending the final i-Like workshop in Newcastle-upon-Tyne, then heading to ABC in Edinburgh and the ISBA World Meeting before returning to Warwick for BAYSM (the Bayesian Young Statisticians’ Meeting). I’ll also be presenting a talk about bayesImageS at the UseR! conference in Brisbane. Titles and abstracts for my talks are below.

This will be my farewell tour of the UK, as I’ll be relocating back to Australia after an amazing four years as a postdoc at the University of Warwick. After UseR!, I’ll be taking up a lectureship in the School of Mathematics and Statistics and the National Institute for Applied Statistics Research Australia (NIASRA) at the University of Wollongong.

The R package gputools has been consumed in the CRANpocalypse, but version 1.1 and earlier can still be downloaded as a source package from the archive. In order to compile it for macOS 10.12.6 (Sierra), you will need to install version 8 of the CUDA Toolkit as well as version 8.2.1 of the Xcode command-line tools. Even then, there are some major configuration issues that need to be dealt with. For the exceptionally brave, the excruciating details are below…

My second R package, serrsBayes, is now available on CRAN. serrsBayes uses a sequential Monte Carlo (SMC) algorithm to separate an observed spectrum into 3 components: the peaks $s_i(\tilde\nu)$; baseline $\xi_i(\tilde\nu)$; and additive white noise $\epsilon_{i,j} \sim \mathcal{N}(0, \sigma^2_\epsilon)$:

$\mathbf{y}_i = \xi_i(\tilde\nu) + s_i(\tilde\nu) + \boldsymbol\epsilon_i$

More details about the model and SMC algorithm are available in my preprint on arXiv (Moores et al., 2006; v2 2018). The following gives an example of applying serrsBayes to surface-enhanced Raman spectroscopy (SERS) from a previous paper (Gracie et al., 2016).

If you want to destroy my sweater
Hold this thread as I walk away

Undone — Weezer

I received an unexpected email about the new version 0.5-0 of bayesImageS:

Dear maintainer,

Please see the problems shown on
<https://cran.r-project.org/web/checks/check_results_bayesImageS.html>.

A new version 0.5-0 of my R package bayesImageS is now available on CRAN. To accompany it is a revision to my paper with Kerrie and Tony, “Scalable Bayesian inference for the inverse temperature of a hidden Potts model.” (Moores, Pettitt & Mengersen, arXiv:1503.08066v2). This paper introduces the parametric functional approximate Bayesian (PFAB) algorithm (the ‘p’ is silent…), which is a form of Bayesian indirect likelihood (BIL).

Ella Kaye on Ella Kaye

Computational Bayesian statistics

Bayes' Food Cake

A bit of statistics, a bit of cakes.

RWeekly.org - Blogs to Learn R from the Community

Computational Bayesian statistics

Richard Everitt's blog

Computational Bayesian statistics

Let's Look at the Figures

David Firth's blog

Nicholas Tierney

Computational Bayesian statistics

Musings, useful code etc. on R and data science

Another Astrostatistics Blog

The random musings of a reformed astronomer ...

Darren Wilkinson's research blog

Statistics, computing, data science, Bayes, stochastic modelling, systems biology and bioinformatics

Computational Bayesian statistics

Igor Kromin

Computational Bayesian statistics

Statisfaction

I can't get no

Xi'an's Og

an attempt at bloggin, nothing more...

Sam Clifford

Postdoctoral Fellow, Bayesian Statistics, Aerosol Science