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Activity Number: 449 - Recent Advances in Change-Point Detection and Segmentation
Type: Invited
Date/Time: Wednesday, August 1, 2018 : 8:30 AM to 10:20 AM
Sponsor: Section on Nonparametric Statistics
Abstract #326752
Title: Detection and Estimation of Local Signals
Author(s): David O Siegmund*
Companies: Stanford University
Keywords: change-points, broken line, detection and estimation

I will discuss a general framework for detection of local signals, primarily defined by change-points, in sequences of data. Changes can occur continuously, e.g., a change in the slope of a regression line, or discontinuously, e.g., a jump in the level of a process. A motivating example of jump discontinuities is provided by copy number variation (CNV), while slope changes appear to be appropriate for some historical temperature and rainfall records. Theoretical results will be illustrated by simulations and applications. Confidence regions for the change-points and problems associated with dependent observations will also be discussed. Aspects of this research involve collaboration with Fang Xiao, Li Jian, Liu Yi, Nancy Zhang, Benjamin Yakir and Li (Charlie) Xia.

Authors who are presenting talks have a * after their name.

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