Monitoring correlation change in a sequence of random variables

DOI10.1016/j.jspi.2012.06.007zbMath1251.62025OpenAlexW2165576713MaRDI QIDQ715600

Pedro Galeano, Dominik Wied

Publication date: 30 October 2012

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/2003/29399

zbMATH Keywords

Gaussian processesthreshold functiononline detection

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Applications of statistics to actuarial sciences and financial mathematics (62P05) Measures of association (correlation, canonical correlation, etc.) (62H20) Monte Carlo methods (65C05) Inference from stochastic processes (62M99)

Related Items (14)

Sequential change point detection in high dimensional time series ⋮ Adaptive Change Point Monitoring for High-Dimensional Data ⋮ On the application of new tests for structural changes on global minimum-variance portfolios ⋮ BACKWARD CUSUM FOR TESTING AND MONITORING STRUCTURAL CHANGE WITH AN APPLICATION TO COVID-19 PANDEMIC DATA ⋮ Inference for post-change parameters after sequential CUSUM test under AR(1) model ⋮ A Likelihood Ratio Approach to Sequential Change Point Detection for a General Class of Parameters ⋮ A monitoring procedure for detecting structural breaks in factor copula models ⋮ Monitoring test for stability of copula parameter in time series ⋮ Sequential monitoring of the tail behavior of dependent data ⋮ Modified tests for change points in variance in the possible presence of mean breaks ⋮ Anomaly detection: a functional analysis perspective ⋮ A new approach for open‐end sequential change point monitoring ⋮ A nonparametric test for a constant correlation matrix ⋮ Robust online-surveillance of trend-coherence in multivariate data streams: the similar trend monitoring (STM) procedure

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