Ricerca di contatti, progetti,
corsi e pubblicazioni

Introduction to Bayesian Computing

Persone

Mira A.

Docente titolare del corso

Descrizione

Prerequisites: students need to have had an introduction to the Bayesian paradigm: prior, likelihood and posterior distribution. Topics that will be covered: Advanced Bayesian inference, Markov chains, Monte Carlo simulation, Importance sampling, Markov chain Monte Carlo (MCMC) methods, Adaptive MCMC, MCMC convergence diagnostics, Approximate Bayesian Computation.

Obiettivi

The students will be able to estimate a complex Bayesian model and to provide corresponding uncertainty quantifications. COURSE PREREQUISITES Students need to have passed the exam “Introduction to Data Science”

Modalità di insegnamento

In presenza

Impostazione pedagogico-didattica

Weekly lectures will be complemented with tutorials and practicals (with R statistical software)

Modalità d’esame

A final exam worth 100% of the final grade.

Offerta formativa

Prerequisito