Document Type
Discussion Paper
Publication Date
5-1-1989
CFDP Number
906
CFDP Pages
24
Abstract
The problem considered here is that of using a data-driven procedure to select a good estimate from a class of linear estimates indexed by a discrete parameter. In contrast to other papers on this subject, we consider models with heteroskedastic errors. The results apply to model selection problems in linear regression and to nonparametric regression estimation via series estimators, nearest neighbor estimators, and local regression estimators, among others. Generalized C L , cross-validation, and generalized cross-validation procedures are analyzed.
Recommended Citation
Andrews, Donald W.K., "Asymptotic Optimality of Generalized CL, Cross-Validation, and Generalized Cross-Validation in Regression with Heteroskedastic Errors" (1989). Cowles Foundation Discussion Papers. 1150.
https://elischolar.library.yale.edu/cowles-discussion-paper-series/1150