Discovery of statistical equivalence classes using computer algebra

被引:10
|
作者
Goergen, Christiane [1 ]
Bigatti, Anna [2 ]
Riccomagno, Eva [2 ,3 ]
Smith, Jim Q. [4 ,5 ]
机构
[1] Max Planck Inst Math Sci, Leipzig, Germany
[2] Univ Genoa, Dipartimento Matemat, I-16146 Genoa, Italy
[3] CNR, Inst Intelligent Syst Automat, Rome, Italy
[4] Univ Warwick, Dept Stat, Coventry CV5 7AL, W Midlands, England
[5] British Lib, Alan Turing Inst, 96 Euston Rd, London NW1 2DB, England
基金
英国工程与自然科学研究理事会;
关键词
Graphical models; Staged tree models; Computer algebra; Ideal decomposition; Algebraic statistics; CHAIN EVENT GRAPHS; BAYESIAN NETWORKS;
D O I
10.1016/j.ijar.2018.01.003
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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. (C) 2018 Elsevier Inc. All rights reserved.
引用
收藏
页码:167 / 184
页数:18
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