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Last edited on
Apr 14, 2020 by JJ
.

Seminar (SS 2019)

Bayesian statistics

Preliminary discussion:
Monday, April 15th, 2019, 15:15,
MΛTHEMΛTIKON, INF 205, 4th floor, SR 7

Time and location of the seminar:
The seminar will be held as a Blockseminar on two days end of June, beginning of July 2019.

Contact:
Jan JOHANNES <johannes[at]math.uni-heidelberg.de>
Questions, please directly by email or by using the contact form.

Language:
The seminar will be in English if there is at least one non-German speaking participant. Otherwise the presentations will be in German.

Seminar program:

Talk Subject
  Robert, The Bayesian choice, Springer, 2007.
1. Introduction (Chapter 1)
2./3. Decision theory (Chapter 2)
4. Bayesian point estimation (Chapter 4)
5. Tests and confidence regions (Chapter 5)
6. Bayesian calculations (Chapter 6)
  Ghosal and van der Vaart, Fundamentals of nonparametric Bayesian inference, Cambridge, 2017.
7. Priors on function spaces (Chapter 2)
8. Priors on spaces of probabilty measures (Chapter 3)
9. Dirichlet process (Chapter 4)
10. Consistency (Section 6.1)
11. Doob’s theorem and inconsistency (Section 6.2-6.3)
12. Schwarz’s theorem (Section 6.4)
13. Alternative approaches (Section 6.8)
14. Consistency: examples (Chapter 7)
15.- Contraction rates (Chapter 8)
16.- Contraction rates: examples (Chapter 9)
17.- Bernstein-von Mises Theorem (Chapter 12)

Area:
Applied Mathematics, Stochastics
Please register for the seminar by using MÜSLI.

Requirements:
Statistics I, Probability theory I

Literature:
Robert, The Bayesian choice, Springer, 2007.
Klenke, Probability theory. A comprehensive course, Springer, 2008.
Berger, Statistical Decision Theory and Bayesian Analysis, 2nd ed., Springer 1980.
Ghoshal and van der Vaart, Fundamentals of Nonparametric Bayesian Inference, Cambridge University Press, 2016

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