Tree-structured model diagnostics for linear regression

被引：0
|
作者：
Xiaogang Su
Chih-Ling Tsai
Morgan C. Wang
机构：
[1] University of Central Florida,Department of Statistics and Actuarial Science
[2] University of California,Graduate School of Management
来源：
Machine Learning | 2009年 / 74卷
关键词：
AIC; CART; Heteroscedasticity; Linear models; Regression trees;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper studies model diagnostics for linear regression models. We propose two tree-based procedures to check the adequacy of linear functional form and the appropriateness of homoscedasticity, respectively. The proposed tree methods not only facilitate a natural assessment of the linear model, but also automatically provide clues for amending deficiencies. We explore and illustrate their uses via both Monte Carlo studies and real data examples.
引用
收藏
页码：111 / 131
页数：20
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