Dear colleagues, Transmitting Science is offering the course "Introduction to Bayesian Inference in Practice".
Course webpage: https://www.transmittingscience.com/courses/statistics-and-bioinformatics/introduction-bayesian-inference-practice/ Instructors: Dr. Daniele Silvestro [1] (ETH Zürich, Switzerland) and Dr. Tobias Andermann [2] (University of Uppsala, Sweden) Course overview: On this course, we will outline the relevant concepts and basic theory of Bayesian methods, but the focus of the course will be to learn how to perform Bayesian inference in practice. We will demonstrate how to implement the most common algorithms to estimate parameters based on posterior probabilities, such as Markov Chain Monte Carlo samplers, and how to build hierarchical models. We will also touch upon hypothesis testing using Bayes factors and Bayesian variable selection. The course will take a learn-by-doing approach, in which participants will implement their own MCMCs using R or Python (templates for both languages will be provided). After completion of the course, the participants will have gained a better understanding of how the main Bayesian methods implemented in many programs used in biological research work. Participants will also learn how to model at least basic problems using Bayesian statistics and how to implement the necessary algorithms to solve them. The aim is that, by the end of the course, each participant will have written their own MCMC - from scratch! For more information, please contact us at [email protected] Best wishes Sole -- Soledad De Esteban-Trivigno, PhD Director Transmitting Science www.transmittingscience.com/courses Bluesky @soledeesteban.bsky.social X @SoleDeEsteban Orcid: https://orcid.org/0000-0002-2049-0890 Links: ------ [1] https://www.transmittingscience.com/instructors/daniele-silvestro/ [2] https://www.transmittingscience.com/instructors/tobias-andermann/ [[alternative HTML version deleted]] _______________________________________________ R-sig-phylo mailing list - [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-phylo Searchable archive at http://www.mail-archive.com/[email protected]/
