English

Discovery of statistical equivalence classes using computer algebra

Statistics Theory 2017-05-29 v1 Computation Statistics Theory

Abstract

Discrete statistical models supported on labelled event trees can be specified using so-called interpolating polynomials which are generalizations of generating functions. These admit a nested representation. 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.

Keywords

Cite

@article{arxiv.1705.09457,
  title  = {Discovery of statistical equivalence classes using computer algebra},
  author = {Christiane Görgen and Anna Bigatti and Eva Riccomagno and Jim Q. Smith},
  journal= {arXiv preprint arXiv:1705.09457},
  year   = {2017}
}

Comments

26 pages, 9 figures

R2 v1 2026-06-22T19:59:46.307Z