An Extension of the Results of Asmussen and Edwards on Collapsibility in Contingency Tables
本文扩展了Asmussen和Edwards关于列联表可压缩性的条件，针对可分解对数线性模型，结合图论算法找出可压缩的子表，减少专家系统中概率网络的运算量。
Asmussen & Edwards (1983) defined necessary and sufficient conditions for collapsibility of a hierarchical log linear model for a multidimensional contingency table. We have shown that for decomposable log linear models these conditions can be combined with various graph-theoretic algorithms to provide useful classes of sub-tables which are collapsible onto. In particular, the SAHR algorithm finds the minimal set onto which the model can be collapsed and which contains a sub-table of interest. In the context of expert systems, by reducing a probabilistic influence network onto only the relevant nodes, the algorithms reduce the required computation and simplify interpretation