Title

Using Intraslice Covariances For Improved Estimation Of The Central Subspace In Regression

Keywords

Inverse regression estimation; Sliced inverse regression; Sufficient dimension reduction

Abstract

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. © 2006 Biometrika Trust.

Publication Date

3-1-2006

Publication Title

Biometrika

Volume

93

Issue

1

Number of Pages

65-74

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1093/biomet/93.1.65

Socpus ID

33644973603 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/33644973603

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