Nonparametric detection of changepoints for sequentially observed data

DOI10.1016/0304-4149(94)90051-5zbMath0801.62070OpenAlexW2077604548MaRDI QIDQ1336982

Dietmar Ferger

Publication date: 30 November 1994

Published in: Stochastic Processes and their Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0304-4149(94)90051-5

zbMATH Keywords

finite horizoninvariance principletriangular arrayprobability of false alarmmartingale maximal-inequalitiesnonparametric stopping ruleweak convergence of two-parameter stochastic processes

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Central limit and other weak theorems (60F05) Stopping times; optimal stopping problems; gambling theory (60G40) Martingales with continuous parameter (60G44) Functional limit theorems; invariance principles (60F17) Optimal stopping in statistics (62L15) Nonparametric inference (62G99)

Related Items (6)

MONITORING PROCEDURES TO DETECT UNIT ROOTS AND STATIONARITY ⋮ Hybrid Bayesian procedures for automatic detection of change-points ⋮ Approximations for the time of change and the power function in change-point models ⋮ Estimators for the Time of Change in Linear Models ⋮ Weighted Dickey-Fuller processes for detecting stationarity ⋮ Random Walks with Drift – A Sequential Approach

Cites Work

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• Probability Inequalities for Sums of Bounded Random Variables
• On Weak Convergence of Stochastic Processes with Multidimensional Time Parameter
• Procedures for Reacting to a Change in Distribution
• A Bayes Approach to a Quality Control Model
• CONTINUOUS INSPECTION SCHEMES

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