In this note, we shortly survey some recent approaches on the approximation of the Bayes factor used in Bayesian hypothesis testing and in Bayesian model choice. In particular, we reassess importance sampling, harmonic mean sampling, and nested sampling from a unified perspective.

Aim This study is aimed to diagnose and analyze strongyloidiasis in a population of an endemic area of Iran using nested-PCR, coupled with parasitological methods. Background Screening of strongyloidiasis infected people using reliable diagnostic techniques are essential to decrease the mortality and morbidity associated with this infection. Molecular methods have been proved to be highly sen...

MOTIVATION Model selection is a fundamental part of the scientific process in systems biology. Given a set of competing hypotheses, we routinely wish to choose the one that best explains the observed data. In the Bayesian framework, models are compared via Bayes factors (the ratio of evidences), where a model's evidence is the support given to the model by the data. A parallel interest is infer...

A stratified version of nested case-control sampling which we call "countermatching" is presented. This design uses data available for all cohort members to obtain a sample for collecting additional information in a case-control substudy. Hitherto the only stratified sampling design for such studies has involved matching of controls to cases with respect to confounding variables. However, in so...

The speed-up in program running time is investigated for problems of parameter estimation with nested sampling Monte Carlo methods. The example used in this study is to extract a polarisation observable from event-by-event data from meson photoproduction reactions. Various implementations of the basic algorithmwere compared, consisting of combinations of single threaded versus multi-threaded, a...

Nested sampling estimates directly how the likelihood function relates to prior mass. The evidence (alternatively the marginal likelihood, marginal density of the data, or the prior predictive) is immediately obtained by summation. It is the prime result of the computation, and is accompanied by an estimate of numerical uncertainty. Samples from the posterior distribution are an optional byprod...

The nested sampling algorithm has been shown to be a general method for calculating the pressure-temperature-composition phase diagrams of materials. While the previous implementation used single-particle Monte Carlo moves, these are inefficient for condensed systems with general interactions where single-particle moves cannot be evaluated faster than the energy of the whole system. Here we enh...

Biodiversity is often ill-defined and subjectively surveyed, resulting in inefficient and ambiguous estimates. Strengths and deficiencies of prevailing survey techniques are appraised through a review of selected literature. Analogies with forest inventory are used to suggest options for more efficient and rigorous biodiversity assessment. Techniques such as variable-probability and model-based...