Bartlett Correctability of Empirical Likelihood for Time Series

N. Chan, Li Liu
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引用次数: 10

Abstract

A desirable feature of the empirical likelihood (EL) method is its Bartlett correctability. Previous studies have only demonstrated that the Bartlett correctability of EL for independent cases. This paper considers the Bartlett correctability of EL in time series models. The validity of the formal Edgeworth expansion for the EL ratio statistic in the short-memory case is established and through meticulous calculations, a closed form expansion for the statistic is deduced. The order of the coverage error of the EL confidence region for time series is obtained based on such an Edgeworth expansion of the EL ratio statistic. It is further demonstrated that the coverage error can be reduced by an order of magnitude after using a Bartlett correction. Finally, a simulation study is presented to illustrate the Bartlett correctability of EL in the short-memory case.
时间序列经验似然的Bartlett可校正性
经验似然(EL)方法的一个令人满意的特点是它的巴特利特校正性。以往的研究仅证明了独立病例的Bartlett校正性。本文考虑了时间序列模型中EL的Bartlett校正性。建立了短记忆情况下EL比值统计量的形式Edgeworth展开式的有效性,并通过细致的计算,推导出该统计量的封闭形式展开式。基于这种EL比率统计量的Edgeworth展开式,得到时间序列EL置信区域的覆盖误差阶数。进一步证明,使用Bartlett校正后,覆盖误差可以降低一个数量级。最后,通过仿真研究说明了短记忆情况下EL的Bartlett纠错性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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