Discovering statistical equivalence classes of discrete statistical models using computer algebra

Eva Riccomagno (University of Genova)

Friday 12th January, 2018 15:00-16:00 Seminar room 311B

Abstract

Discrete statistical models supported on labeled event trees can be specified using so-called interpolating polynomials which are generalizations of generating functions. These admit a nested representation which is a notion formalized in this paper. A new algorithm exploits the primary decomposition of monomial ideals associated with an interpolating polynomial to quickly compute all nested representations of that polynomial. It hereby determines an important subclass of all trees representing the same statistical model. To illustrate this method we analyze the full polynomial equivalence class of a staged tree representing the best fitting model inferred from a real-world dataset.

Joint work with Anna Bigatti (University of Genova, Italy), Christiane Goergen (Max-Planck-Institute for Mathematics in the Sciences, Leipzig, Germany) and Jim Q. Smith (The University of Warwick, UK)

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