The first part of the module covers the basic concepts of Bayesian Inference such as prior and posterior distribution, Bayesian estimation, model choice and forecasting. These concepts are also ...

Bayesian Inference: Bayes theorem, prior, posterior and predictive distributions, conjugate models (Normal-Normal, Poisson-Gamma, Beta-Binomial), Bayesian point estimation, credible intervals and ...

Probabilistic models, such as hidden Markov models or Bayesian networks, are commonly used to model biological data. Much of their popularity can be attributed to the existence of efficient and ...