Segmentation and Estimation of Change-point Models: False Positive Control and Confidence Regions
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AbstractTo segment a sequence of independent random variables at an unknown number of change-points, we introduce new procedures that are based on thresholding the likelihood ratio statistic, and give approximations for the probability of a false positive error when there are no change-points. We also study confidence regions based on the likelihood ratio statistic for the change-points and joint confidence regions for the change-points and the parameter values. Applications to segment array CGH data are discussed.
Acceptance Date01/05/2019
All Author(s) ListXiao Fang, Jian Li, David Siegmund
Journal nameAnnals of Statistics
Year2020
Volume Number48
Issue Number3
Pages1615 - 1647
ISSN0090-5364
eISSN2168-8966
LanguagesEnglish-United States

Last updated on 2020-30-10 at 01:38