SEGMENTATION AND ESTIMATION OF CHANGE-POINT MODELS: FALSE POSITIVE CONTROL AND CONFIDENCE REGIONS

被引：21

作者：

Fang, Xiao ^{[1
]}

Li, Jian ^{[2
]}

Siegmund, David ^{[3
]}

机构：

[1] Chinese Univ Hong Kong, Dept Stat, Hong Kong, Peoples R China

[2] Adobe Syst, San Jose, CA USA

[3] Stanford Univ, Dept Stat, Stanford, CA 94305 USA

来源：

ANNALS OF STATISTICS | 2020年 / 48卷 / 03期

基金：

美国国家科学基金会;

关键词：

Array CGH analysis; change-points; confidence regions; exponential families; likelihood ratio statistics; COPY-NUMBER; BINARY SEGMENTATION; TAIL PROBABILITIES; ALGORITHMS; MAXIMA; TESTS;

D O I：

10.1214/19-AOS1861

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

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, 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.

引用

页码：1615 / 1647

页数：33

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