Title
Tree-structured model diagnostics for linear regression
Abstract
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.
Journal Title
Machine Learning
Volume
74
Issue/Number
2
Publication Date
1-1-2009
Document Type
Article
First Page
111
Last Page
131
WOS Identifier
ISSN
0885-6125
Recommended Citation
"Tree-structured model diagnostics for linear regression" (2009). Faculty Bibliography 2000s. 2193.
https://stars.library.ucf.edu/facultybib2000/2193
Comments
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