Algebraic statistics: tables and networks

This lecture covers algebraic statistics, contingency tables, and networks, focusing on the Fienberg advantage. It discusses networked data, testing model goodness of fit, log-linear models for contingency tables, and algorithmic and theoretical considerations. The lecture explores the geometry and algebra of log-linear models, Markov bases, and the application of algebraic statistics in testing for reciprocation effect. It also delves into stochastic blockmodels, latent variants, and the mixture of log-linear models. The lecture concludes with discussions on structural considerations, model equivalences, and the application of algebraic statistics in connectome data.