Statistics and Data Science Seminar
Sonja Petrovic
UIC, MSCS
An invitation to algebraic statistics
Abstract: Algebraic statistics is a maturing discipline whose main focus is the study of statistical models using the tools from algebraic geometry and computational algebra. The main concept is that statistical models are algebraic varieties. Algebraic approach can be used to provide Markov bases for the models, or to compute the maximum likelihood degree. Some of the best studied models so far are contingency tables, conditional independence models and graphical models including latent class.
Algebraic statistics has also found applications in computational biology and phylogenetics. Some recent work shows that it can be used as a powerful tool for phylogenetic tree reconstruction and for model identifiability problems.
This will be an introductory talk to explain some of the main concepts of the field, illustrated on a few examples.
Wednesday February 25, 2009 at 4:15 PM in SEO 612