M9201 Bayesian methods

Faculty of Science
Autumn 2014
Extent and Intensity
0/2. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: z (credit).
Teacher(s)
prof. RNDr. Gejza Wimmer, DrSc. (lecturer)
Guaranteed by
prof. RNDr. Gejza Wimmer, DrSc.
Department of Mathematics and Statistics – Departments – Faculty of Science
Supplier department: Department of Mathematics and Statistics – Departments – Faculty of Science
Timetable of Seminar Groups
M9201/01: Tue 12:00–13:50 M3,01023
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
To show the basis of Bayesian statistical methods;
Bayesian estimators and inferences;
comparisom of Bayesian and frequentist methods;
computational methods for evaluation the aposterior density (approximation of integrals, simulation methods, Monte-Carlo integration);
I-divergence and information obtained from the experiment
Syllabus
  • Bayes' theorem and aposterior density.
  • Bayes' formula for discrete and continuous random variables.
  • Linking rule.
  • I-divergence and information obtained from the experiment.
  • Noninformative priors.
  • Computational methods for evaluation of aposterior density.
  • Conjugate systems of prior densities.
  • Simulation methods and Monte-Carlo integration.
  • MCMC methods.
  • Bayesian (point and interval) estimation, inferencies, predictions.
Literature
  • PÁZMAN, Andrej. Bayesovská štatistika (Bayesian statistics). Bratislava: Univerzita Komenského Bratislava, 2003, 100 pp. ISBN 80-223-1821-3. info
  • DAVISON, Anthony C. Statistical Models. Cambridge University Press, 2003. info
  • HUŠKOVÁ, Marie. Bayesovské metody (Bayesian methods). Praha: Univerzita Karlova v Praze, 1985, 93 pp. info
Teaching methods
theoretical preparation, reading of papers, presentations, separate programming
Assessment methods
individual presentation of a part of the theme (topic)
Language of instruction
Czech
Further Comments
Study Materials
The course is taught once in two years.
The course is also listed under the following terms Autumn 2012, Autumn 2016.
  • Enrolment Statistics (Autumn 2014, recent)
  • Permalink: https://is.muni.cz/course/sci/autumn2014/M9201