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

Zhensheng Huang, Zhen Pang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

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.
Original languageEnglish
Pages (from-to)276-284
Number of pages9
JournalJournal of Multivariate Analysis
Volume105
Issue number1
DOIs
Publication statusPublished - 1 Feb 2012
Externally publishedYes

Keywords

  • Confidence interval
  • Empirical likelihood
  • Partially linear single-index model
  • Right censoring

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Numerical Analysis
  • Statistics and Probability

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