Functional estimation for time series: Uniform convergence properties

DOI10.1016/S0378-3758(97)00133-XzbMath0951.62074WikidataQ127152347 ScholiaQ127152347MaRDI QIDQ1299530

Paul Doukhan, Patrick Ango Nze

Publication date: 23 August 1999

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

zbMATH Keywords

mixingautoregressive processes

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Nonparametric estimation (62G05) Stationary stochastic processes (60G10) General nonlinear regression (62J02)

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Evaluation for moments of a ratio with application to regression estimation, Root-\(n\) consistent estimation of the marginal density in semiparametric autoregressive time series models, The almost sure central limit theorems for the maxima of sums under some new weak dependence assumptions, Nonparametric estimation of the hazard function under dependence conditions, Nonparametric estimation of the maximum hazard under dependence conditions, Uniformly root-\(n\) consistent density estimators for weakly dependent invertible linear proc\-esses, On the Uniform Strong Consistency of Local Polynomial Regression Under Dependence Conditions, Weak dependence beyond mixing and asymptotics for nonparametric regression, Estimation and test of linearity for a class of additive nonlinear models, A Projection-Based Nonparametric Test of Conditional Quantile Independence

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