Ultrahigh-dimensional sufficient dimension reduction with measurement error in covariates

Li-Pang Chen

Statistics & Probability Letters, 2021, vol. 168, issue C

Abstract: Analysis of sufficient dimension reduction (SDR) is an important topic and has attracts our attention in decades. Several methods have been proposed based on simple settings. In applications, however, the ultrahigh-dimensional setting with p≫n and covariate measurement error usually appear in the dataset, and it is not trivial to adopt the conventional methods to handle this problem. In this paper, we consider the SDR with both the ultrahigh-dimensional setting and covariate measurement error incorporated simultaneously. The theoretical results of the proposed method are established.

Keywords: Cumulative mean estimation; Distance correlation; Feature selection; Measurement error; Ultrahigh-dimension (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1016/j.spl.2020.108931

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