Using intraslice covariances for improved estimation of the central subspace in regression

• 成果类型: Article
• 署名作者: Cook, RD; Ni, LQ
• 署名单位: University of Minnesota System; University of Minnesota Twin Cities; State University System of Florida; University of Central Florida
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/93.1.65
• 发表日期: 2006
• 页码: 6574
• 关键词: sliced inverse regression; Dimension Reduction

摘要

Popular methods for estimating the central subspace in regression require slicing a continuous response. However, slicing can result in loss of information and in some cases that loss can be substantial. We use intraslice covariances to construct improved inference methods for the central subspace. These methods are optimal within a class of quadratic inference functions and permit chi-squared tests of conditional independence hypotheses involving the predictors. Our experience gained through simulation is that the new method is never worse than existing methods, and can be substantially better.