Empirical likelihood-based inference in a partially linear model for longitudinal data

查看全文 作　　者：XUE LiuGen~(1+) & ZHU LiXing~2 1 College of Applied Sciences, Beijing University of Technology, Beijing 100022, China;2 Department of Mathematics, Hong Kong Baptist University, Hong Kong, China

出　　处：《Science China Mathematics》索引2008年第51卷第1期,共16页

基　　金：The first author was supported by the National Natural Science Foundation of China (Grant No. 10571008);the Natural Science Foundation of Beijing (Grant No. 1072004);the Science and Technology Development Project of Education Committee of Beijing City (Grant No. KM200510005009);The second author was supported by a grant of the Research Grant Council of Hong Kong (Grant No. HKBU7060/04P) 摘　　要：A partially linear model with longitudinal data is considered, empirical likelihood to infer- ence for the regression coefficients and the baseline function is investigated, the empirical log-likelihood ratios is proven to be asymptotically chi-squared, and the corresponding confidence regions for the pa- rameters of interest are then constructed. Also by the empirical likelihood ratio functions, we can obtain the maximum empirical likelihood estimates of the regression coefficients and the baseline function, and prove the asymptotic normality. The numerical results are conducted to compare the performance of the empirical likelihood and the normal approximation-based method, and a real example is analysed. 关键词：PARTIALLY linear model empirical LIKELIHOOD CONFIDENCE REGION longitudinal data

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Empirical likelihood-based inference in a partially linear model for longitudinal data

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