Bayesian Statistics

Basic information

Workload: 

45 hours

Prerequisite: 

 Mathematical Statistics

Syllabus: 

Statistical models: interchangeability, partial interchangeability, sufficiency and invariance. Conjugated analysis, reference priorities and asymptotic theory. Credibility intervals and regions. Comparison of models: hypothesis tests, Bayes factors, discrepancy measures and predictive distributions.

Bibliography

Mandatory: 

·       Bernardo, J. M. e Smith, A. F. M. (1994). Bayesian Theory. Wiley;
·       Robert, C. (1995). The Bayesian Choice. Springer-Verlag.
·       Gamerman, D., & Lopes, H. F. (2006). Markov chain Monte Carlo: stochastic simulation for Bayesian inference. Chapman and Hall/CRC.

Complementary: 

·       DeGroot, M. H. (1970). Optimal Statistical Decisions. McGraw-Hill.
·       A. Gelman, J.B. Carlin, H.S. Stern and D.B. Rubin (2004). Bayesian Data Analysis, Second Edition. Chapman & Hall.
·       Migon, H. S., Gamerman, D., & Louzada, F. (2014). Statistical inference: an integrated approach. CRC press.
·       Hoff, P. D. (2009). A first course in Bayesian statistical methods. Springer Science & Business Media.
·       Berger, J. O. (2013). Statistical decision theory and Bayesian analysis. Springer Science & Business Media.