Weighted envelope estimation to handle variability in model selection
成果类型：
Article
署名作者：
Eck, D. J.; Cook, R. D.
署名单位：
University of Minnesota System; University of Minnesota Twin Cities
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.1093/biomet/asx035
发表日期：
2017
页码：
743749
关键词：
摘要：
Envelope methodology can provide substantial efficiency gains in multivariate statistical problems, but in some applications the estimation of the envelope dimension can induce selection volatility that may mitigate those gains. Current envelope methodology does not account for the added variance that can result from this selection. In this article, we circumvent dimension selection volatility through the development of a weighted envelope estimator. Theoretical justification is given for our estimator, and the validity of the residual bootstrap for estimating its asymptotic variance is established. A simulation study and real-data analysis illustrate the utility of our weighted envelope estimator.