On the consistency of coordinate-independent sparse estimation with BIC

JOURNAL OF MULTIVARIATE ANALYSIS

卷:112

Article

Zou, Changliang^1,2  Chen, Xin³ 

[1] Nankai Univ, Sch Math Sci, LPMC, Tianjin 300071, Peoples R China

[2] Nankai Univ, Dept Stat, Tianjin 300071, Peoples R China

[3] Natl Univ Singapore, Dept Stat & Appl Probabil, Singapore 117548, Singapore

关键词: BIC;    Central subspace;    Consistency;    Coordinate-independent;    Sufficient dimension reduction;    Variable selection;   

DOI  :  10.1016/j.jmva.2012.04.014

来源: Elsevier

【 摘 要 】

Chen et al. (2010) [1] propose a unified method - coordinate-independent sparse estimation (CISE) - that is able to simultaneously achieve sparse sufficient dimension reduction and screen out irrelevant and redundant variables efficiently. However, its attractive features depend on the appropriate choice of the tuning parameter. In this note, we re-examine the Bayesian information criterion (BIC) in sufficient dimension reduction and provide a heuristic derivation. Furthermore, the CISE with BIC is shown to be able to identify the true model consistently. (C) 2012 Elsevier Inc. All rights reserved.

【 授权许可】

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