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On estimation efficiency of the central mean subspace
Author(s) -
Ma Yanyuan,
Zhu Liping
Publication year - 2014
Publication title -
journal of the royal statistical society: series b (statistical methodology)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.523
H-Index - 137
eISSN - 1467-9868
pISSN - 1369-7412
DOI - 10.1111/rssb.12044
Subject(s) - estimator , subspace topology , dimension (graph theory) , variance (accounting) , estimation , sample (material) , variance components , dimensionality reduction , component (thermodynamics) , mathematics , econometrics , computer science , statistics , artificial intelligence , economics , chemistry , physics , accounting , chromatography , pure mathematics , thermodynamics , management
Summary We investigate the estimation efficiency of the central mean subspace in the framework of sufficient dimension reduction. We derive the semiparametric efficient score and study its practical applicability. Despite the difficulty caused by the potential high dimension issue in the variance component, we show that locally efficient estimators can be constructed in practice. We conduct simulation studies and a real data analysis to demonstrate the finite sample performance and gain in efficiency of the proposed estimators in comparison with several existing methods.