U.S.-Hungary Statistics Research: Topics in Change Point and Unit Root Analysis; Rates of Convergence, Permutations and Bootstrap

这个由犹他州大学的Lajos Horvath和Piotr Kokoszka以及他们的匈牙利合作伙伴，A。Renyi数学研究所在布达佩斯，研究了几个统计和概率问题有关的检测和分析的非平稳性的各种类型的随机过程。重点是仔细分析的速度收敛的统计利益和相关的置换和引导程序的属性。 来自犹他州大学的初级研究人员也参加了联合研究计划，包括调查变点程序和单位根检验的性质，这是基于重新抽样和二次抽样方法开发的。 这些都是与时间序列检测相关的基本问题。 结果可能有实际应用在经济和金融部门，导致有用的衍生物的属性的GRETUM程序和GRETMAN模型。 例如，研究结果可能会改进股票收益模型，这些模型可以被改进以适应无限的误差方差。该统计研究项目通过使美国和中欧的专家能够联合收割机互补人才并在共同感兴趣和能力强的领域共享研究资源，实现了推进科学知识的计划目标。

This US-Hungarian collaborative project between Lajos Horvath and Piotr Kokoszka of the University of Utah and their Hungarian partners, Istvan Berkes and Endre Csaki of the A. Renyi Institute of Mathematics in Budapest, examines several statistical and probabilistic problems concerned with the detection and analysis of nonstationarities of various types of stochastic processes. Emphasis is on careful analysis of the rates of convergence of the statistics of interest and on the properties of the associated permutation and bootstrap procedures. Junior researchers from the University of Utah also participate.The joint research plan includes an investigation of change point procedures and the properties of unit root tests, that are to be developed based on resampling and subsampling methods. These are fundamental questions associated with the detection of time series. Results may have practical applications in economics and the financial sector by leading to useful derivations of properties of CUSUM procedures and GARCH models. For example, findings may improve models for stock returns that can be refined to accommodate infinite error variance. This statistics research project fulfills the program objective of advancing scientific knowledge by enabling experts in the United States and Central Europe to combine complementary talents and share research resources in areas of strong mutual interest and competence.