吉林大学学报(理学版) ›› 2022, Vol. 60 ›› Issue (6): 1335-1341.

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基于经验似然方法的BINAR(1)过程参数的置信域

刘燕, 肖玉山   

  1. 长春大学 理学院, 长春 130022
  • 收稿日期:2021-12-28 出版日期:2022-11-26 发布日期:2022-11-26
  • 通讯作者: 刘燕 E-mail:liuyan81@ccu.edu.cn

Confidence Regions of Parameters for BINAR(1) Process Based on Empirical Likelihood Methods

LIU Yan, XIAO Yushan   

  1. School of Science, Changchun University, Changchun 130022, China
  • Received:2021-12-28 Online:2022-11-26 Published:2022-11-26

摘要: 考虑将经验似然(EL)方法应用于二维一阶整数值自回归(BINAR(1))过程. 先利用该过程条件最小二乘(CLS)估计量的渐近正态性建立经验似然比(ELR)统计量, 并寻找其极限分布, 以构造参数的置信域, 解决参数的假设检验问题; 然后通过数值模拟对比由EL方法和正态逼近(NA)法计算的参数置信域的覆盖率.

关键词: BINAR(1)过程, EL方法, ELR统计量, 得分函数

Abstract: We considered the application of the  empirical likelihood (EL) method to the bivariate first-order integer-valued autoregressive (BINAR(1)) process. We first established the empirical likelihood ratio (ELR) statistics, discussed and found its limit distribution by using asymptotic normality of the conditional least squares (CLS) estimation of the process, thus constructed the confidence regions of the parameter and solved the problem of hypothesis test of the parameters. Then, the coverage probability of the confidence region of the parameters computed by EL methods and normal approximation (NA) methods was compared through numerical simulation.

Key words: BINAR(1) process, EL methods, ELR statistics, score function

中图分类号: 

  • O211.61