Detection and estimation of structural change in heavy-tailed sequence

DOI10.1080/03610926.2015.1006780zbMath1360.62210OpenAlexW2531828276MaRDI QIDQ2980141

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Publication date: 27 April 2017

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2015.1006780

zbMATH Keywords

bootstrap testchange pointheavy-tailed sequenceratio estimation

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Nonparametric estimation (62G05) Bootstrap, jackknife and other resampling methods (62F40)

Related Items (3)

Ratio detections for change point in heavy tailed observations ⋮ Nuisance-parameter-free changepoint detection in non-stationary series ⋮ Abrupt change in mean using block bootstrap and avoiding variance estimation

Cites Work

• On linear models with long memory and heavy-tailed errors
• The maximum likelihood method for testing changes in the parameters of normal observations
• Bootstrap tests for structural change with infinite variance observations
• Testing for parameter stability in quantile regression models
• Heavy-tailedness and threshold sex determination
• Change-point in the mean of dependent observations
• A bootstrap approximation to a unit root test statistic for heavy-tailed observations.
• The sample autocorrelations of heavy-tailed processes with applications to ARCH
• Change point estimation for continuous-time hidden Markov models
• A new class of models for heavy tailed distributions in finance and insurance risk
• Least‐squares Estimation of an Unknown Number of Shifts in a Time Series
• Point processes, regular variation and weak convergence
• LEAST SQUARES ESTIMATION OF A SHIFT IN LINEAR PROCESSES
• Subsampling the mean of heavy‐tailed dependent observations

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