Contingency Table and Granularity

S. Tsumoto, S. Hirano
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引用次数: 1

Abstract

This paper gives a matrix-theory based approach to a contingency table and shows that sample size gives a strong constraints on its granularity. In the former studies, relations between degree of granularity and dependence of contingency tables are given from the viewpoint of determinantal divisors and sample size. The nature of determinantal divisors shows that the increase of the degree of granularity may lead to that of dependence. However, a constraint on the sample size of a contingency table is very strong, which leads to the evaluation formula where the increase of degree of granularity gives the decrease of dependency. This paper gives a further study of the nature of sample size effect on the degree of dependency in a contingency matrix. The results show that sample size will restrict the nature of matrix in a combinatorial way, which suggests that the dependency is closely related with integer programming.
列联表和粒度
本文给出了一种基于矩阵理论的列联表方法,并证明了样本大小对列联表的粒度有很强的约束。在以往的研究中,从确定性因子和样本量的角度给出列联表的粒度度与相关性的关系。行列式除数的性质表明,粒度度的增加可能导致依赖度的增加。然而,列联表的样本量有很强的约束,这就导致了这样的评价公式:粒度度的增加导致依赖性的降低。本文进一步研究了随机矩阵中样本量对依赖程度的影响。结果表明,样本大小会以组合方式限制矩阵的性质,这表明这种依赖关系与整数规划密切相关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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