A robust inverse regression estimator
Abbreviated Journal Title
Stat. Probab. Lett.
central subspace; inverse regression estimator; sufficient dimension; reduction; SUFFICIENT DIMENSION REDUCTION; Statistics & Probability
A family of dimension reduction methods was developed by Cook and Ni [Sufficient dimension reduction via inverse regression: a minimum discrepancy approach. J. Amer. Statist. Assoc. 100, 410-428.] via minimizing a quadratic objective function. Its optimal member called the inverse regression estimator (IRE) was proposed. However, its calculation involves higher order moments of the predictors. In this article, we propose a robust version of the IRE that only uses second moments of the predictor for estimation and inference, leading to better small sample results. (c) 2006 Elsevier B.V. All rights reserved.
Statistics & Probability Letters
"A robust inverse regression estimator" (2007). Faculty Bibliography 2000s. 7469.