Segmentation and Estimation of Change-point Models: False Positive Control and Confidence Regions
Statistics Theory
2018-10-16 v3 Statistics Theory
Abstract
To 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. 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.
Keywords
Cite
@article{arxiv.1608.03032,
title = {Segmentation and Estimation of Change-point Models: False Positive Control and Confidence Regions},
author = {Xiao Fang and Jian Li and David Siegmund},
journal= {arXiv preprint arXiv:1608.03032},
year = {2018}
}
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48 pages