Corrected empirical likelihood inference for right-censored partially linear single-index model

JOURNAL OF MULTIVARIATE ANALYSIS

卷:105

Article

Huang, Zhensheng^1,2  Pang, Zhen¹ 

[1] Nanyang Technol Univ, Sch Phys & Math Sci, Div Math Sci, Singapore 639798, Singapore

[2] Hefei Univ Technol, Sch Math, Hefei 230009, Peoples R China

关键词: Confidence interval;    Empirical likelihood;    Partially linear single-index model;    Right censoring;   

DOI  :  10.1016/j.jmva.2011.10.002

来源: Elsevier

【 摘 要 】

This article deals with the inference on a right-censored partially linear single-index model (RCPLSIM). The main focus is the local empirical likelihood-based inference on the nonparametric part in RCPLSIM. With a synthetic data approach, an empirical log-likelihood ratio statistic for the nonparametric part is defined and it is shown that its limiting distribution is not a central chi-squared distribution. To increase the accuracy of the confidence interval, we also propose a corrected empirical log-likelihood ratio statistic for the nonparametric function. The resulting statistic is proved to follow a standard chi-squared limiting distribution. Simulation studies are undertaken to assess the finite sample performance of the proposed confidence intervals. A real example is also considered. (C) 2011 Elsevier Inc. All rights reserved.

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