Nonparametric sequential change-point detection for multivariate time series based on empirical distribution functions-Reference-Cited by-同舟云学术

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Nonparametric sequential change-point detection for multivariate time series based on empirical distribution functions

Published:2021-01-01 Issue:1 Volume:15 Page:
ISSN:1935-7524
Container-title:Electronic Journal of Statistics
language:
Short-container-title:Electron. J. Statist.

Author:

Kojadinovic Ivan,Verdier Ghislain

Publisher

Institute of Mathematical Statistics

Subject

Statistics and Probability,Statistics, Probability and Uncertainty

Link

https://projecteuclid.org/download/pdfview_1/euclid.ejs/1611284539

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. The state of cumulative sum sequential change point testing seventy years after Page;Biometrika;2023-12-21

2. Multi‐purpose open‐end monitoring procedures for multivariate observations based on the empirical distribution function;Journal of Time Series Analysis;2023-03-23

3. Online Detection of Regression Model Coefficient Change Points Based on S-BCUSUM;Operations Research and Fuzziology;2023

4. Change point detection for the intraday volatility using functional ARCH and conditional Copula;Communications in Statistics - Simulation and Computation;2022-12-30

5. Monitoring procedures for strict stationarity based on the multivariate characteristic function;Journal of Multivariate Analysis;2021-11

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