Statistical inference for generalized random coefficient autoregressive model
Statistical inference for generalized random coefficient autoregressive model
复制标题
广义随机系数自回归模型的统计推断
DOI：
10.1016/j.mcm.2011.12.002
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发表时间：
2012-10-01
影响因子：
--
通讯作者：
Wang, De-Hui
中科院分区：
文献类型：
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作者：
Zhao, Zhi-Wen;Wang, De-Hui
In this paper, we consider the application of the empirical likelihood method to the generalized random coefficient autoregressive (GRCA) model. The empirical log-likelihood ratio statistics are proposed and the nonparametric versions of the Wilk's theorem are obtained. Furthermore, when the order of the model is 1, we also derive a test statistic to test the stationary-ergodicity based on the conditional least-squares method. Numerical results from simulation studies suggest that the empirical likelihood method is more accurate than the normal approximation-based method of Hwang and Basawa (1998) [1]. Some simulation studies are also conducted to investigate the finite sample performances of the proposed test. (c) 2011 Elsevier Ltd. All rights reserved.
