A robust inverse regression estimator

Liqiang Ni and R. Dennis Cook

Statistics & Probability Letters, 2007, vol. 77, issue 3, 343-349

Abstract: 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.

Keywords: Central; subspace; Inverse; regression; estimator; Sufficient; dimension; reduction (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (2)

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