In the past ten years there has been a dramatic increase of interest in the Bayesian analysis
of finite mixture models. This is primarily because of the emergence of Markov chain Monte …

In this paper we discuss auxiliary variable approaches to Bayesian binary and multinomial
regression. These approaches are ideally suited to automated Markov chain Monte Carlo …

… Michiels S, Koscielny S, Hill C (2005) Prediction of cancer outcome with microarrays: A
multiple random validation strategy. Lancet 365: 488–492. … Lapointe J, Li C, Higgins JP …

We propose a framework for general Bayesian inference. We argue that a valid update of a
prior belief distribution to a posterior can be made for parameters which are connected to …

In many problems in geostatistics the response variable of interest is strongly related to the
underlying geology of the spatial location. In these situations there is often little correlation in …

Upper- and lower-body fat depots exhibit opposing associations with obesity-related metabolic
disease. We defined the relationship between DEXA-quantified fat depots and diabetes/…

1 H Nuclear Magnetic Resonance spectroscopy ( 1 H NMR) is increasingly used to measure
metabolite concentrations in sets of biological samples for top‐down systems biology and …

The stochastic nature of generating eukaryotic transcripts challenges conventional methods
for obtaining and analyzing single-cell gene expression data. In order to address the …

In this paper, we start by reviewing exchangeability and its relevance to the Bayesian approach.
We highlight the predictive nature of Bayesian models and the symmetry assumptions …

… CC Holmes , CC Holmes … Holmes gratefully acknowledges support from the Oxford-Man
Institute, the Alan Turing Institute, the Medical Research Council, UK, and the UK …