Bayesian methods (NMST431)

Arnošt Komárek

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Bayesian methods (NMST431)

Winter semester 2021–22

SIS pages of the course:    ENG    CZE

Jointly taught with prof. RNDr. Marie Hušková, DrSc.

Language of both lectures and all exercise classes is English if and only if there is at least one officially subscribed student who is not enrolled in the Czech study programme.

TIMETABLE

Lecture: Monday 9:00 in K6   
Exercise class: Monday 10:40 in K6   

MATERIALS

Přednáška, prof. Marie Hušková
Slidy 1:     PDF
Slidy 2:     PDF
Slidy 3:     PDF
Slidy 4:     PDF
Slidy 5:     PDF
Slidy 6:     PDF

Přednáška, doc. Arnošt Komárek
Slidy:        PDF        poslední změna: 5.10.2021
R skript:    Vaha_lehkych.R
 

Cvičení, doc. Arnošt Komárek
Cv. 1.11.:      Zadání (PDF)    
Cv. 22.11.:      Poznámky (PDF)        
      R skript (R skript)    Dataset (mastitis.RData)    
Cv. 29.11.:      Zadání (PDF)    Dataset (toenail.txt)    

JAGS SOFTWARE

Next to R, we will also use JAGS (Just Another Gibbs Sampler) which can be downloaded (for various platforms) here (latest version seems optimal, read README first...):

Source code (to compile)
DEB for Debian Linux
Package for Ubuntu Linux
RPM based Linux distributions
Mac OS X
Windows bin

User manual to JAGS can be found here. Installation manual (if needed) is here. Examples of JAGS analyzes are here. As a study material, practical exercises from the short course given at UseR conference can be useful. Solutions to the exercises are here.

To be able to call JAGS from R, package runjags available in a standard way from CRAN is needed.

LITERATURE

Hušková, M. (1985).
Bayesovské metody (course notes in Czech).
Praha: Univerzita Karlova v Praze.     PDF
 
Robert, C. P. (2001, 2007).
The Bayesian Choice: From Decision-Theoretic Foundations
to Computational Implementation, Second Edition.
New York: Springer.     Full PDF (used to be available from the IP addresses of MFF UK)
 
Marin, J.-M., Robert, C. P. (2007).
Bayesian Core: A Practical Approach to Computational Bayesian Statistics.
New York: Springer.     Full PDF (used to be available from the IP addresses of MFF UK)
 
Gelman, A., Carlin, J. B., Stern, H. S., Rubin, D. B., Dunson, D. B. (2014).
Bayesian Data Analysis, Third Edition.
Boca Raton: Chapman & Hall/CRC.     Information on the publisher's web
 
Carlin, B. P., Louis, T. A. (2008).
Bayesian Methods for Data Analysis, Third Edition.
Boca Raton: Chapman & Hall/CRC.     Information on the publisher's web
 
Robert, C. P., Casella, G. (2004).
Monte Carlo Statistical Methods, Second Edition.
New York: Springer.     Information on the publisher's web
 

 

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