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Inference Based on Empirical Likelihood for Varying Coefficient Model with Random Effect
Department of Mathematics, Yancheng Teachers University, Yancheng, China;College of Applied Sciences, Beijing University of Technology, Beijing, China
College of Applied Sciences, Beijing University of Technology, Beijing, China
- 1 Department of Mathematics, Yancheng Teachers University, Yancheng, China;College of Applied Sciences, Beijing University of Technology, Beijing, China
- 2 College of Applied Sciences, Beijing University of Technology, Beijing, China
Open Journal of Statistics·Volume 03 (2013)·Pages 52–59·Published 28 December 2013·DOI10.4236/ojs.2013.36A006
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Abstract
In this article, we develop a statistical inference technique for the unknown coefficient functions in the varying coeffi - cient model with random effect. A residual-adjusted block empirical likelihood (RABEL) method is suggested to inves - tigate the model by taking the within-subject correlation into account. Due to the residual adjustment, the proposed RABEL is asymptotically chi-squared distribution. We illustrate the large sample performance of the proposed method via Monte Carlo simulations and a real data application.
KeywordsVarying Coefficient ModelRandom EffectEmpirical LikelihoodLongitudinal Data
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