Fast robust estimation of prediction error based on resampling

Subscribe to email list

Please select the email list(s) to which you wish to subscribe.

You are here

Fast robust estimation of prediction error based on resampling

TitleFast robust estimation of prediction error based on resampling
Publication TypeJournal Article
Year of Publication2010
AuthorsKhan, JA, Van Aelst, S, Zamar, RH
JournalCOMPUTATIONAL STATISTICS & DATA ANALYSIS
Volume54
Pagination3121-3130
Date PublishedDEC 1
Type of ArticleArticle
ISSN0167-9473
Keywordsbootstrap, Cross-validation, Prediction error, Robustness
AbstractRobust estimators of the prediction error of a linear model are proposed. The estimators are based on the resampling techniques cross-validation and bootstrap. The robustness of the prediction error estimators is obtained by robustly estimating the regression parameters of the linear model and by trimming the largest prediction errors. To avoid the recalculation of time-consuming robust regression estimates, fast approximations for the robust estimates of the resampled data are used. This leads to time-efficient and robust estimators of prediction error. (C) 2010 Elsevier B.V. All rights reserved.
DOI10.1016/j.csda.2010.01.031