Conditional maximum likelihood estimation in negative binomial INGARCH processes with known number of successes when the true parameter is at the boundary of the parameter space
Conditional maximum likelihood estimation in negative binomial INGARCH processes with known number of successes when the true parameter is at the boundary of the parameter space
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DOI：
10.1080/03610926.2018.1476710
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发表时间：
2019-07-03
影响因子：
0.8
通讯作者：
Wang, Xiaoyin
中科院分区：
文献类型：
--
作者：
Cui, Yunwei;Wang, Xiaoyin
在负二项分布定义中成功次数已知的条件下，当真参数位于参数空间的边界时，建立了条件负二项分布的整数值广义自回归条件异方差过程的条件极大似然估计的渐近分布.在此基础上，对模型进行了系数无效性检验。建议的测试进行了研究，通过模拟研究。
The paper establishes the asymptotic distribution of the conditional maximum likelihood estimator for integer-valued generalized autoregressive conditional heteroskedastic (INGARCH) processes of conditional negative binomial distributions, with the number of successes in the definition of the negative binomial distribution being assumed to be known, when the true parameter is at the boundary of the parameter space. Based on the result, coefficient nullity tests are developed for model simplification. The proposed tests are investigated through a simulation study.