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.

引用

页数：7

共 44 条

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