Institute of Mathematics and Statistics
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  • Eesti keel
  • Courses
  • 2025/26 spring
  • Introduction to Bayesian Modeling (LTMS.00.076)

Introduction to Bayesian Modeling 2025/26 spring

  • Pealeht
  • Seminar
  • Viited

Probabilistic programming languages for Bayesian statistical inference

  • Python PyMC, ArviZ for visualization
  • R RStan, for more 'R-like experience' use rstanarm or brms
  • Julia Turing.jl

Tartu Ülikoolis varasemalt toimunud Bayesi kursuseid:

  • ...-2016 Bayesi statistika Markovi ahelatega, konspekt
  • 2023-2024 Sissejuhatus Bayesi mudelitesse (3 EAP)
  • 2025 Praktiline Bayesi statistika, GitHub

Literature (in no particular order)

  • Gelman, Carlin, Stern, Dunson, Vehtari, Rubin (2014). Bayesian Data Analysis (BDA). 3rd edition. Here is the book webpage and a free PDF version.
  • Schervish (1995). Theory of Statistics.
  • Robert (2007). The Bayesian Choice: From Decision-Theoretic Foundations to Computational Implementation. 2nd edition.
  • Hoff (2009). A First Course in Bayesian Statistical Methods.
  • Kruschke (2015). Doing Bayesian data analysis: a tutorial with R, JAGS, and Stan. 2nd edition. Free online book is available in the university's network.
  • McElreath (2020). Statistical rethinking: a Bayesian course with examples in R and Stan.
  • Ghosal, Van Der Vaart (2017). Fundamentals of Nonparametric Bayesian Inference.
  • Institute of Mathematics and Statistics
  • Faculty of Science and Technology
  • University of Tartu
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