Asymptotic properties of maximum likelihood estimators in models with multiple change points

DOI10.3150/09-BEJ232zbMath1220.62021arXiv1102.5224MaRDI QIDQ637080

Heping He, Thomas A. Severini

Publication date: 2 September 2011

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1102.5224

zbMATH Keywords

consistencyconvergence rateKullback-Leibler distancechange-point fractioncommon parameterwithin-segment parameter

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Asymptotic distribution theory in statistics (62E20)

Related Items (8)

Convergence in distribution of multiple change point estimators ⋮ Consistency of minimum description length model selection for piecewise stationary time series models ⋮ Asymptotic properties of pseudo maximum likelihood estimators and test in semi-parametric copula models with multiple change points ⋮ Asymptotic properties of \(M\)-estimators based on estimating equations and censored data in semi-parametric models with multiple change points ⋮ A semiparametric maximum likelihood ratio test for the change point in copula models ⋮ Some Nonparametric Tests for Change-Point Detection Based on the ℙ-ℙ and ℚ-ℚ Plot Processes ⋮ Mechanistic Analysis of Challenge–Response Experiments ⋮ Asymptotic properties of semiparametric \(M\)-estimators with multiple change points

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