Partial envelopes for efficient estimation in multivariate linear regression
成果类型：
Article
署名作者：
Su, Zhihua; Cook, R. Dennis
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/asq063
发表日期：
2011
页码：
133146
关键词：
摘要：
We introduce the partial envelope model, which leads to a parsimonious method for multivariate linear regression when some of the predictors are of special interest. It has the potential to achieve massive efficiency gains compared with the standard model in the estimation of the coefficients for the selected predictors. The partial envelope model is a variation on the envelope model proposed by Cook et al. (2010) but, as it focuses on part of the predictors, it has looser restrictions and can further improve the efficiency. We develop maximum likelihood estimation for the partial envelope model and discuss applications of the bootstrap. An example is provided to illustrate some of its operating characteristics.