Combinatorics in Pearson residuals
Shusaku Tsumoto, Shoji Hirano · International Journal of Knowledge Engineering and Soft Data Paradigms · 2013
This paper focuses on residual analysis of statistical independence of multiple variables from the viewpoint of linear algebra and combinatorics. The results show that multidimensional residuals are represented as linear sum of determinants of 2 × 2 submatrices, which can be viewed as information granules measuring the degree of statistical dependence. Furthermore, all the elements of information granules have combinatorial characteristics of index sets.