Three predictive power measures for generalized linear models: The entropy coefficient of determination, the entropy correlation coefficient and the regression correlation coefficient

被引：8

作者：

Eshima, Nobuoki ^{[1
]}

Tabata, Minoru ^{[2
]}

机构：

[1] Oita Univ, Fac Med, Dept Biostat, Oita 8795593, Japan

[2] Osaka Prefecture Univ, Grad Sch Engn, Dept Math Sci, Osaka 5998531, Japan

来源：

COMPUTATIONAL STATISTICS & DATA ANALYSIS | 2011年 / 55卷 / 11期

关键词：

Categorical data analysis; Generalized linear model; Predictive power measure; Entropy; RESIDUAL VARIATION; VARIABLES;

D O I：

10.1016/j.csda.2011.05.018

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this paper, three predictive power measures for generalized linear models (GLMs) are compared, and the utility of the entropy correlation coefficient (ECC) and the entropy coefficient of determination (ECD) is demonstrated. First, ECC, ECD and the regression correlation coefficient (RCC) are briefly explained. Second, relationships of the three measures are discussed, and the necessary and sufficient condition under which ECC and RCC are equal is deduced. Third, ECC and ECD are discussed for GLMs with canonical links and polytomous response variables, and an analysis of the effects of factors in GLMs is given. Finally, a discussion of the conclusions of this study is provided. (C) 2011 Elsevier B.V. All rights reserved.

引用

页码：3049 / 3058

页数：10

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