Description
Bayesian methods are being increasingly employed in many different areas of research in the physical sciences. In astrophysics, models are used to make predictions to be compared to observations. These observations offer information that is incomplete and uncertain, so the comparison has to be pursued by following a probabilistic approach. With contributions from leading experts, this volume covers the foundations of Bayesian inference, a description of computational methods, and recent results from their application to areas such as exoplanet detection and characterisation, image reconstruction, and cosmology. It appeals to both young researchers seeking to learn about Bayesian methods as well as to astronomers wishing to incorporate these approaches in their research areas. It provides the next generation of researchers with the tools of modern data analysis that are already becoming standard in current astrophysical research.
Table of Contents
1. Bayesian inference and computation: a beginner's guide Brendon J. Brewer; 2. Inverse problems in astronomy Jean-Luc Starck; 3. Bayesian inference in extra-solar planet searches Phil Gregory; 4. Bayesian cosmology Roberto Trotta; 5. An introduction to objective Bayesian statistics José M. Bernardo.
