Change point estimation by local linear smoothing under a weak dependence condition

DOI10.3103/S1066530707010036zbMath1283.60061MaRDI QIDQ2440595

Yanyan Li

Publication date: 19 March 2014

Published in: Mathematical Methods of Statistics (Search for Journal in Brave)

zbMATH Keywords

infinitely divisible distributionscentral limit theoremnonparametric regressionlocal linear regressionstationary sequenceschange pointweakly dependent sequencesLindeberg theorem

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Stationary stochastic processes (60G10) Functional limit theorems; invariance principles (60F17)

Related Items (3)

Adaptive density estimation of stationary \(\beta\)-mixing and \(\tau\)-mixing processes ⋮ Change point estimators by local polynomial fits under a dependence assumption ⋮ Ratio tests for variance change in nonparametric regression

Cites Work

• Unnamed Item
• Change-points in nonparametric regression analysis
• Variable bandwidth and local linear regression smoothers
• Kernel-type estimators of jump points and values of a regression function
• Change point estimation using nonparametric regression
• A new weak dependence condition and applications to moment inequalities
• New dependence coefficients. Examples and applications to statistics
• Change point estimation for a weakly dependent sequence
• Change point estimation by local linear smoothing
• About the Berry-Esseen theorem for weakly dependent sequences
• Conditional convergence to infinitely divisible distributions with finite variance
• The asymptotic distributions of kernel estimators of the mode
• Some Limit Theorems for Stationary Processes

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