On testing common indices for two multi-index models: A link-free approach

JOURNAL OF MULTIVARIATE ANALYSIS

卷:136

Article

Liu, Xuejing¹  Yu, Zhou²  Wen, Xuerong Meggie¹  Paige, Robert¹ 

[1] Missouri Univ Sci & Technol, Dept Math & Stat, Rolla, MO 65409 USA

[2] E China Normal Univ, Sch Finance & Stat, Shanghai 200062, Peoples R China

关键词: Multi-index models;    Sufficient dimension reduction;    Sliced inverse regression;    Sliced average variance estimation;    Directional regression;   

DOI  :  10.1016/j.jmva.2015.01.009

来源: Elsevier

【 摘 要 】

We propose a link-free procedure for testing whether two multi-index models share identical indices via the sufficient dimension reduction approach. Test statistics are developed based upon three different sufficient dimension reduction methods: (i) sliced inverse regression, (ii) sliced average variance estimation and (iii) directional regression. The asymptotic null distributions of our test statistics are derived. Monte Carlo studies are performed to investigate the efficacy of our proposed methods. A real-world application is also considered. (C) 2015 Elsevier Inc. All rights reserved.

【 授权许可】

Free