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Activity Number: 495 - Changepoints: Making an Impact
Type: Topic Contributed
Date/Time: Wednesday, July 31, 2019 : 10:30 AM to 12:20 PM
Sponsor: Royal Statistical Society
Abstract #304968
Title: Detection and Estimation of Local Signals
Author(s): David Siegmund* and Xiao Fang
Companies: and Chinese University of Hong Kong
Keywords: changepoint; broken line; segmentation

We study the maximum score statistic to detect and estimate local signals in the form of change-points in the level, slope, or other property of a sequence of observations, and to segment the sequence when there appear to be multiple changes. We find that when observations are dependent, the change-points can lead to upwardly biased estimates of autocorrelations, resulting in a sometimes serious loss of power. Applications to temperature variations, atmospheric CO2 levels, disease incidence, and fluctuations in the size of animal populations, illustrate the general theory.

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

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