partially supported by National Natural Science Foundation of China(11671267);Scientific Research Level Improvement Quota Project of Capital University of Economics and Business and Scientific Research Foundation for Young Teachers of Capital University of Economics and Business(00591654490336);partially supported by the National Natural Science Foundation of China(Nos.11301212,11401146);partially supported by the National Natural Science Foundation of China Grants(No.11231010,11171330 and 11021161);Key Laboratory of RCSDS,CAS(No.2008DP173182);partly supported by National Natural Science Foundation of China(11271155);Specialized Research Fund for the Doctoral Program of Higher Education(20110061110003);Scientific Research Fund of Jilin University(201100011);Jilin Province Natural Science Foundation(20101596)
Panel count data occur in many clinical and observational studies and in some situations the observation process is informative. In this article, we propose a new joint model for the analysis of panel count data with ...
Supported by National Natural Science Foundation of China(Grant Nos.10990012 and 11021161)
This paper investigates the weighted least absolute deviations estimator(WLADE) for causal and invertible periodic autoregressive moving average(PARMA) models. Asymptotic normality of the estimator is derived unde...
supported by International Cooperation Projects (2010DFA31790) of Chinese Ministry of Science and Technology;the fund of Central China Normal University for Ph.D students (No. 2009023);supported by the National Natural Science Foundation of China Grants(No. 10731010, 10971015 and 11021161);the National Basic Research Program of China (973 Program) (No.2007CB814902);Key Laboratory of Random Complex Structures and Data Science, Academy of Mathematics& Systems Science, Chinese Academy of Sciences (No. 2008DP173182)
Recurrent event data often arises in biomedical studies, and individuals within a cluster might not be independent. We propose a semiparametric additive rates model for clustered recurrent event data, wherein the cova...