Empirical likelihood confidence regions in time series models
Empirical likelihood confidence regions in time series models
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DOI：
10.1093/biomet/84.2.395
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发表时间：
1997-06
期刊：
影响因子：
2.7
通讯作者：
Anna Clara Monti
中科院分区：
文献类型：
--
作者：
Anna Clara Monti
摘要本文发展了时间序列模型的经验似然性。应用Whittle估计方法，从近似独立的观测值得到平稳时间序列参数的M-估计，即周期图纵坐标。该估计量用于获得经验似然比，其渐近分布为x2，并且可用于构造置信区域。Bartlett校正的程序也提出了建议。最后，通过仿真研究了经验似然置信域的小样本性质。
SUMMARY This paper develops empirical likelihood in time series models. By application of Whittle's estimation method, one obtains an M-estimator of the parameter of a stationary time series from approximately independent observations, the periodogram ordinates. This estimator is used to obtain an empirical likelihood ratio which is asymptotically distributed as x2 and which can be used to construct confidence regions. A procedure for the Bartlett correction is also proposed. Finally, small sample properties of the empirical likelihood confidence regions are explored through a simulation.