Monitoring changes in the error distribution of autoregressive models based on Fourier methods
Monitoring changes in the error distribution of autoregressive models based on Fourier methods
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DOI：
10.1007/s11749-011-0265-z
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发表时间：
2012-12
期刊：
影响因子：
1.3
通讯作者：
Z. Hlávka;M. Hušková;C. Kirch;S. Meintanis
中科院分区：
文献类型：
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作者：
Z. Hlávka;M. Hušková;C. Kirch;S. Meintanis
我们开发了一种程序，用于监控自回归时间序列的误差分布的变化，同时控制序贯检验的总体规模。与参考的标准方法不同，该方法利用了适当估计残差的经验特征函数。研究了检验统计量在零假设和备选方案下的极限行为。由于渐近零分布包含未知参数，为了实际进行检验，提出了一种新的Bootstrap方法，并给出了相应的有限样本性能结果。事实证明，该方法不仅能够检测出分布的变化，而且还能检测到回归系数的变化。
We develop a procedure for monitoring changes in the error distribution of autoregressive time series while controlling the overall size of the sequential test. The proposed procedure, unlike standard procedures which are also referred to, utilizes the empirical characteristic function of properly estimated residuals. The limit behavior of the test statistic is investigated under the null hypothesis as well as under alternatives. Since the asymptotic null distribution contains unknown parameters, a bootstrap procedure is proposed in order to actually perform the test and corresponding results on the finite–sample performance of the new method are presented. As it turns out the procedure is not only able to detect distributional changes but also changes in the regression coefficient.