Truncated sequential change-point detection based on renewal counting processes. II

DOI10.1016/j.jspi.2008.08.021zbMath1161.62045OpenAlexW2095153336MaRDI QIDQ1011531

Allan Gut, Josef G. Steinebach

Publication date: 8 April 2009

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

Full work available at URL: https://doi.org/10.1016/j.jspi.2008.08.021

zbMATH Keywords

Wiener processstopping timerenewal counting processfirst passage timestrong approximationincrementschange-pointsequential testextreme value asymptoticstraining period

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Extreme value theory; extremal stochastic processes (60G70) Statistics of extreme values; tail inference (62G32) Brownian motion (60J65) Stopping times; optimal stopping problems; gambling theory (60G40) Sequential statistical analysis (62L10) Functional limit theorems; invariance principles (60F17) Optimal stopping in statistics (62L15) Renewal theory (60K05)

Related Items (9)

Asymptotic delay times of sequential tests based on \(U\)-statistics for early and late change points ⋮ Asymptotics for \(p\)-value based threshold estimation in regression settings ⋮ The shark fin function: asymptotic behavior of the filtered derivative for point processes in case of change points ⋮ Moving Sum Data Segmentation for Stochastic Processes Based on Invariance ⋮ Asymptotics for increments of stopped renewal processes ⋮ Sequential testing of gradual changes in the drift of a stochastic process ⋮ Multi-scale detection of rate changes in spike trains with weak dependencies ⋮ Structural breaks in time series ⋮ Sequential detection of gradual changes in the location of a general stochastic process

Cites Work

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• Truncated Sequential Change‐point Detection based on Renewal Counting Processes
• Delay time in monitoring jump changes in linear models
• CONTINUOUS INSPECTION SCHEMES
• Testing for changes in the mean or variance of a stochastic process under weak invariance
• \(U\)-statistics for sequential change detection.

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