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史晓平博士学术报告

  发布日期:2017-7-16  浏览量:290


报告题目: A consistent and powerful graph based change-point test for high-dimensional data

: 史晓平博士(加拿大汤姆森河大学(Thompson Rivers University),助理教授)

报告时间: 2017717(周一)  16:30-17:30

报告地点: 磬苑校区数学科学学院H306

报告摘要:Modeling high-dimensional time series is necessary in many fields such as network evolution, image analysis and text analysis. For instance, the time of cell divisions can be accessed utilizing an automatic embryo monitoring system by a time-lapse observation. When a cell divides at some time point, the distribution of pixel values in the corresponding frame will change, and hence the detection of cell divisions can be formulated as a multiple change-point problem. The aim is to automatically detect multiple change points: the time points of first, second and third division cycles. The change-point detection is carried out by using a Bayesian-type statistic based on the shortest Hamiltonian path, and the change-point is estimated by Ratio Cut.  A permutation procedure is applied to approximate the significance of Bayesian-type statistics. The change-point test is proved to be consistent, and an error probability in change-point estimation is provided. Compared to the test of Chen and Zhang (2015) based on the minimum spanning tree, the new test is particularly powerful against alternatives with a shift in variance and is accurate in change-point estimation, as shown in simulation studies. Its applicability in tracking cell division is illustrated.

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                                              数学科学学院

                                            2017716

专家简介: 史晓平,2002年毕业于重庆大学应用数学本科专业,而后加入合肥工业大学担任助教职务。2008年获得中国科学技术大学概率统计硕士学位,随后赴加拿大约克大学攻读统计博士学位并于2011年获得博士学位。紧接着在多伦多大学从事博士后研究,随后分别在约克大学和圣弗朗西斯·格扎维埃大学任教,2016年加入汤姆森河大学,担任助理教授职务。主要从事领域包括分布的鞍点近似、复合似然推断、变量选择、基于图论方法的变点检测以及图像去噪声等。许多成果已在Proceedings of the National Academy of Sciences(美国国家科学院院刊2)Statistica SinicaComputational Statistics and Data AnalysisComputational StatisticsJournal of Mathematical Analysis and ApplicationsScience China MathematicsCanadian Journal of StatisticsStatistics and Probability LettersAustralian and New Zealand Journal of StatisticsJournal of Statistical Theory and Practice等杂志上发表。进一步信息可参见其网页https://kamino.tru.ca/experts/home/main/bio.html?id=xshi

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