Abstract
In this paper, the authors consider the empirical likelihood method for a first-order generalized random coefficient integer-valued autoregressive process. The authors establish the log empirical likelihood ratio statistic and obtain its limiting distribution. Furthermore, the authors investigate the point estimation, confidence regions and hypothesis testing for the parameters of interest. The performance of empirical likelihood method is illustrated by a simulation study and a real data example.
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This work was supported by the National Natural Science Foundation of China under Grant Nos. 11871028 and 11731015.
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Cheng, J., Wang, X. & Wang, D. Empirical Likelihood for a First-Order Generalized Random Coefficient Integer-Valued Autoregressive Process. J Syst Sci Complex 36, 843–865 (2023). https://doi.org/10.1007/s11424-023-1051-1
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DOI: https://doi.org/10.1007/s11424-023-1051-1