On functional processes with multiple discontinuities
On functional processes with multiple discontinuities
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DOI：
10.1111/rssb.12493
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发表时间：
2022-03
期刊：
影响因子：
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通讯作者：
Jialiang Li;Yaguang Li;T. Hsing
中科院分区：
文献类型：
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作者：
Jialiang Li;Yaguang Li;T. Hsing
我们考虑的问题，估计多个变化点的功能数据处理。在科学和金融领域，有许多例子表明，利息过程可能会受到均值突然变化的影响。不靠近任何变化点的过程数据可以通过通常的非参数平滑方法进行分析。然而，接近变化点的数据和包含最相关的结构突变信息需要特别小心处理。本文考虑了一种半核方法，该方法解决了变化的总数，位置和跳跃大小的推断。所提出的程序的收敛速度和渐近分布的结果进行了深入研究。仿真进行了检查的方法的性能，和一些真实的数据集进行了分析，以提供一个说明。
We consider the problem of estimating multiple change points for a functional data process. There are numerous examples in science and finance in which the process of interest may be subject to some sudden changes in the mean. The process data that are not in a close vicinity of any change point can be analysed by the usual nonparametric smoothing methods. However, the data close to change points and contain the most pertinent information of structural breaks need to be handled with special care. This paper considers a half‐kernel approach that addresses the inference of the total number, locations and jump sizes of the changes. Convergence rates and asymptotic distributional results for the proposed procedures are thoroughly investigated. Simulations are conducted to examine the performance of the approach, and a number of real data sets are analysed to provide an illustration.