A Geometric Approach to Compare Variables in a Regression Model
作者:
Johan Bring,
期刊:
The American Statistician
(Taylor Available online 1996)
卷期:
Volume 50,
issue 1
页码: 57-62
ISSN:0003-1305
年代: 1996
DOI:10.1080/00031305.1996.10473543
出版商: Taylor & Francis Group
关键词: Coefficient of determination;Perpendicular projection;Relative importance;Standardized regression coefficients;tvalues.
数据来源: Taylor
摘要:
Geometry is a very useful tool for illustrating regression analysis. Despite its merits the geometric approach is seldom used. One reason for this might be that there are very few applications at an elementary level. This article gives a brief introduction to the geometric approach in regression analysis, and then geometry is used to shed some light on the problem of comparing the “importance” of the independent variables in a multiple regression model. Even though no final answer of how to assess variable importance is given, it is still useful to illustrate the different measures geometrically to gain a better understanding of their properties.
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