XIIth School of Cosmology
 
September 15 - 20, 2014IESC, Cargèse
STRUCTURE FORMATION AFTER PLANCK
their impact in the study of galaxies and
Cosmology

Bayesian inference and model selection

Roberto TROTTA
Imperial College London

Chapters

  1. Principle of probability
  2. Classical statistics vs Bayesian
  3. Likelihood, prior and posterior
  4. Bayes theorem: meaning and application
  5. Bayesian inference
  6. MCMC
  7. Hierarchical models
  8. Bayesian model selection: theory
  9. Bayesian model selection vs hypothesis testingensing basics

    Abstract

    These lectures will give a short introduction to the fundamentals of Bayesian inference and its application to simple but representative problems. Numerical methods such as Markov Chain Monte Carlo will be introduced and their practical workings illustrated. The Bayesian approach to model selection via Bayesian model comparison will be explained and contrasted with Frequentist hypothesis testing. 

    Bibliography

    Program