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- SIS page: NMST431
- Schedule: on Monday 15:40-17:10 in
classroom K8 and 17:20-18:50 in
classroom K2
- Language: materials in English, instructed in Czech
(unless anybody requires English)
- Instructor e-mail: vavraj@karlin.mff.cuni.cz
- Lecture web page: https://www.karlin.mff.cuni.cz/~komarek/vyuka/2025_26/nmst431-2025.html
- Note: Division into “lecture” and “exercise class”
is just formal. The style of teaching (“lecture”/“exercise class”) will
change dynamically over the semester. At the beginning of the semester
exercises will become lectures. The first exercise will probably be by
the end of October.
Credit
- Satisfactory solution to given assignments by the prescribed
deadline.
(If your solution will not be satisfactory enough, you
might be asked for revision.)
Send your solution via email to
address vavraj@karlin.mff.cuni.cz.
Recommended
form: Rmarkdown output
(PDF or HTML) or Sweave
Overview
- Topic: Bayesian approach when the posterior is
known
- Assignment: Discover the true posterior
distribution, construct credible intervals and compare them with
approximation via Monte Carlo approach. Full
assignment in PDF
- Deadline: Monday 3
November 9:00
- Topic: How to use JAGS (Just Another Gibbs Sampler)
for estimating hierarchical models
- Assignment: Using Gibbs sampling approximate the
posterior distribution of model parameters of logistic regression with
random intercepts. The intercepts are treated as additional secondary
parameters. Full
assignment in PDF
- Deadline: None - solved together during exercise
class, but there is Exercise 2.5
Homework (10-30
November)
- Topic: Try JAGS for yourself on a simple regression
model
- Assignment: Full
assignment in PDF
- Deadline: Monday 1
December 9:00