Journal of Applied Mathematics

  • J. Appl. Math.
  • Volume 2013, Special Issue (2013), Article ID 792196, 10 pages.

Block Empirical Likelihood for Longitudinal Single-Index Varying-Coefficient Model

Yunquan Song, Ling Jian, and Lu Lin

Full-text: Open access

Abstract

In this paper, we consider a single-index varying-coefficient model with application to longitudinal data. In order to accommodate the within-group correlation, we apply the block empirical likelihood procedure to longitudinal single-index varying-coefficient model, and prove a nonparametric version of Wilks’ theorem which can be used to construct the block empirical likelihood confidence region with asymptotically correct coverage probability for the parametric component. In comparison with normal approximations, the proposed method does not require a consistent estimator for the asymptotic covariance matrix, making it easier to conduct inference for the model's parametric component. Simulations demonstrate how the proposed method works.

Article information

Source
J. Appl. Math., Volume 2013, Special Issue (2013), Article ID 792196, 10 pages.

Dates
First available in Project Euclid: 14 March 2014

Permanent link to this document
https://projecteuclid.org/euclid.jam/1394807763

Digital Object Identifier
doi:10.1155/2013/792196

Mathematical Reviews number (MathSciNet)
MR3115276

Zentralblatt MATH identifier
06950871

Citation

Song, Yunquan; Jian, Ling; Lin, Lu. Block Empirical Likelihood for Longitudinal Single-Index Varying-Coefficient Model. J. Appl. Math. 2013, Special Issue (2013), Article ID 792196, 10 pages. doi:10.1155/2013/792196. https://projecteuclid.org/euclid.jam/1394807763


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