Exponential and polynomial tailbounds for change-point estimators

DOI10.1016/S0378-3758(00)00148-8zbMath0997.62018MaRDI QIDQ5929945

Dietmar Ferger

Publication date: 14 November 2002

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

zbMATH Keywords

change-point estimatorconvergence in lawmartingale maximal inequalitiespolynomial tail boundsrates of convergenceweighted empirical process

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Linear regression; mixed models (62J05) Inequalities; stochastic orderings (60E15) Order statistics; empirical distribution functions (62G30)

Related Items (14)

Weighted Least Squares Estimators for a Change-Point ⋮ Change Point Estimation in Regression Models with Fixed Design ⋮ Change-point detection for long-range dependent sequences in a general setting ⋮ Convergence in distribution of multiple change point estimators ⋮ Asymptotic properties of maximum likelihood estimators in models with multiple change points ⋮ Optimal rate of convergence for nonparametric change-point estimators for nonstationary sequences ⋮ Consistency of change point estimators for symmetrical stable distribution with parameters shift ⋮ Strong convergence rate of estimators of change point and its application ⋮ Multiple change-point estimation with U-statistics ⋮ Rates of convergence for the change-point estimator for long-range dependent sequences ⋮ Detection of change-points near the end points of long-range dependent sequences ⋮ A continuous mapping theorem for the argmax‐functional in the non‐unique case ⋮ Convergence rates for estimating a change-point with long-range dependent sequences ⋮ Inference for single and multiple change-points in time series

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