Change point estimators by local polynomial fits under a dependence assumption

DOI10.1016/j.jmva.2008.02.036zbMath1151.62032OpenAlexW2028728576MaRDI QIDQ957317

Degui Li, Jia Chen, Zheng Yan Lin

Publication date: 27 November 2008

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2008.02.036

zbMATH Keywords

functional limit theoremchange point\(\alpha \)-mixinglocal polynomial fitsrandom design model

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20) Central limit and other weak theorems (60F05) Functional limit theorems; invariance principles (60F17)

Related Items (4)

Change point estimation in regression model with response missing at random ⋮ Kink estimation in stochastic regression with dependent errors and predictors ⋮ A piecewise polynomial trend against long range dependence ⋮ Jump detection in time series nonparametric regression models: a polynomial spline approach

Cites Work

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• REGRESSION QUANTILES FOR TIME SERIES
• Weak Convergence of Probability Measures on the Function Space $C\lbrack 0, \infty)$

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