An estimator of the number of change points based on a weak invariance principle

DOI10.1016/S0167-7152(00)00155-3zbMath0979.62065WikidataQ126803029 ScholiaQ126803029MaRDI QIDQ5933615

Christoph Kühn

Publication date: 18 February 2002

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

zbMATH Keywords

invariance principlechange pointschange in meanlinear processespartial sumsrenewal processesSchwarz criterion

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Non-Markovian processes: estimation (62M09) Functional limit theorems; invariance principles (60F17)

Related Items (7)

On consistency of minimum description length model selection for piecewise autoregressions ⋮ Moving Sum Data Segmentation for Stochastic Processes Based on Invariance ⋮ Estimating nonlinear regression with and without change-points by the LAD method ⋮ Non-monotonic penalizing for the number of structural breaks ⋮ Two-stage data segmentation permitting multiscale change points, heavy tails and dependence ⋮ Rejoinder on: ``Extensions of some classical methods in change point analysis ⋮ Structural breaks in time series

Cites Work

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• Invariance principles for renewal processes
• Estimating the number of change-points via Schwarz' criterion
• Estimating the dimension of a model
• Detection of changes in linear sequences
• Estimating the number of change points in a sequence of independent normal random variables
• An approximation of partial sums of independent RV'-s, and the sample DF. I
• Testing for changes in the mean or variance of a stochastic process under weak invariance

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