Graphical Models and Probabilistic Reasoning
Timo Koski, John M. Noble · Wiley series in probability and statistics · 2009
This chapter contains sections titled: Introduction Axioms of probability and basic notations The Bayes update of probability Inductive learning Interpretations of probability and Bayesian networks Learning as inference about parameters Bayesian statistical inference Tossing a thumb-tack Multinomial sampling and the Dirichlet integral Notes Exercises: Probabilistic theories of causality, Bayes' rule, multinomial sampling and the Dirichlet density