Empirical likelihood for single-index models with responses missing at random

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)1187-1207
Journal / PublicationScience China Mathematics
Volume59
Issue number6
Publication statusPublished - 1 Jun 2016
Externally publishedYes

Abstract

The missing response problem in single-index models is studied, and a bias-correction method to infer the index coefficients is developed. Two weighted empirical log-likelihood ratios with asymptotic chisquare are derived, and the corresponding empirical likelihood confidence regions for the index coefficients are constructed. In addition, the estimators of the index coefficients and the link function are defined, and their asymptotic normalities are proved. A simulation study is conducted to compare the empirical likelihood and the normal approximation based method in terms of coverage probabilities and average lengths of confidence intervals. A real example illustrates our methods.

Research Area(s)

  • confidence region, empirical likelihood, index coefficient, missing response, single-index model