Online multivariate changepoint detection with type I error control and constant time/memory updates per series

被引：0
|
作者：
Hahn, Georg [1 ]
机构：
[1] Univ Lancaster, Dept Stat, Lancaster LA1 4YF, England
来源：
STATISTICS & PROBABILITY LETTERS | 2022年 / 181卷
关键词：
Constant time update; Multiple testing; Multivariate changepoint detection; CHANGE-POINT ESTIMATION; TIME-SERIES;
D O I：
10.1016/j.spl.2021.109258
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：
This article presents a simple algorithm for online multivariate changepoint detection of a mean in rare changepoint settings. The algorithm is based on a modified cusum statistic and guarantees control of the type I error on any false discoveries, while featuring O(1) time and O(1) memory updates per series as well as a proven detection delay. (C) 2021 Elsevier B.V. All rights reserved.
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页数：7
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