Bartlett correction of frequency domain empirical likelihood for time series with unknown innovation variance
Publication in refereed journal

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摘要The Bartlett correction is a desirable feature of the likelihood inference, which yields the confidence region for parameters with improved coverage probability. This study examines the Bartlett correction for the frequency domain empirical likelihood (FDEL), based on the Whittle likelihood of linear time series models. Nordman and Lahiri (Ann Stat 34:3019–3050, 2006) showed that the FDEL does not have an ordinary Chi-squared limit when the innovation is non-Gaussian with unknown variance, which restricts the use of the FDEL inference in time series. We show that, by profiling the innovation variance out of the Whittle likelihood function, the FDEL is Chi-squared-distributed and Bartlett correctable. In particular, the order of the coverage error of the confidence region can be reduced from O(n- 1) to O(n- 2).
出版社接受日期19.07.2019
著者Chen K., Chan N.H., Yau C.Y.
期刊名稱Annals of the Institute of Statistical Mathematics
出版年份2020
月份10
卷號72
期次5
出版社Springer
頁次1159 - 1173
國際標準期刊號0020-3157
電子國際標準期刊號1572-9052
語言英式英語

上次更新時間 2020-26-11 於 00:28