• Course code:63563
  • Credits:6
  • Semester: winter
  • Contents

Brief introduction to Bayesian statistics. Prior. Posterior. Likelihood. Conjugacy. Stan software for Bayesian inference.

MCMC methods. Random number generators. Markov Chains. Monte Carlo. Rejection sampling. Gibbs sampling. Metropolis-Hastings.
 

Statistical models. GLM. Hierarchical modelling. Discrete choice models. Time-series models. Mixture models. Gaussian processes.

Statistics in practice. Choosing priors. Model selection. Model evaluation. Diagnostics. Interpreting statistical models. Reporting statistical results.

Advanced computation. Hamiltonian Monte Carlo. Laplace approximation. Variational Bayes.

  • Study programmes
  • Distribution of hours per semester
45
hours
lectures
30
hours
laboratory work
  • Professor
Assist. Prof. dr. Jure Demšar
Instructor
Room:R3.61 - Kabinet
details