3 papers
astro-ph.IM2026
A space of inference spaces in the space sciences - Parametric Bayesian inference in astronomy, cosmology and particle physics
Johannes Buchner
A sample of parametric Bayesian inference applications from astronomy, cosmology and particle physics is studied, augmented by mock data sets and toy problems. The parameter spaces…
stat.CO2026
First analytical coverage bounds of a fully specified nested sampling algorithm
Johannes Buchner
Nested sampling is a Monte Carlo algorithm for posterior estimation and Bayesian model comparison. It maintains a population of live points sampled from the prior, and at each…
stat.CO2026
Mode Collapse in Nested Sampling
Johannes Buchner
Nested Sampling is a Monte Carlo algorithm enabling posterior estimation and Bayesian model comparison, and is especially robust in multi-modal posteriors. This is because nested s…