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

Authors
Journal
Journal of Multivariate Analysis
0047-259X
Publisher
Elsevier
Publication Date
Volume
105
Issue
1
Identifiers
DOI: 10.1016/j.jmva.2011.10.002
Keywords
  • Confidence Interval
  • Empirical Likelihood
  • Partially Linear Single-Index Model
  • Right Censoring
Disciplines
  • Logic
  • Mathematics

Abstract

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.

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