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The first-order random coefficient integer valued autoregressive process with the occasional level shift random noise based on dual empirical likelihood |
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| Authors: | Shuxia Zhang Boping Tian Yanpeng Li Mingjun Yao |
| Institution: | 1. Department of Statistics, School of Mathematics and Statistics, Jiangsu Normal University, Xuzhou, P.R. China;2. Department of Mathematics, Harbin Institute of Technology, Harbin, P.R. China;3. Department of General Surgery, DongChangFu People’s Hospital, Liaocheng, P.R. China |
| Abstract: | AbstractThis paper investigates the first-order random coefficient integer valued autoregressive process with the occasional level shift random noise based on dual empirical likelihood. The limiting distribution of log empirical likelihood ratio statistic is constructed. Asymptotic convergence and confidence region results of empirical likelihood ratio are given. Hypothesis testing is considering, and maximum empirical likelihood estimation for parameter is acquired. Simulations are given to show that the maximum empirical likelihood estimation is more efficient than the conditional least squares estimation. |
| Keywords: | Empirical likelihood random coefficient semi-parametric asymptotic distribution logistic regression limit theory |