独立随机序列均值多变点的非参数检测
A Nonparametric Test for Multiple Changes in the Mean of Independent Random Series
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摘要: 本文考虑独立随机序列均值多变点的检测与估计问题, 提出一种非参数的检验方法, 给出其渐近分布, 同时亦给出了变点位置的估计, 并证明了变点个数估计的一致性. Monte Carlo试验研究了该检验统计量的有限样本性质, 结果表明该统计量对于厚尾误差具有较好势和经验水平. 最后将文中所给的非参数检验方法应用到鲁北化工(LBC)股票价格数据中, 结果表明, 文中所给统计量可以准确检验出多变点并进行估计.Abstract: A nonparametric procedure is proposed to detect multiple changes in the mean of independent random series and the asymptotic distribution is derived. Simultaneously, the estimators for the locations of the change points are obtained. Moreover, the performance of the test is studied by Monte Carlo simulation, which demonstrates that the proposed test has high powers and good sizes for heavy-tailed innovations. Finally, the feasibility of the proposed test is illustrated by the application on the LBC data of stock prices.