On the Uniform Strong Consistency of Local Polynomial Regression Under Dependence Conditions

DOI10.1081/STA-120025386zbMath1028.62020OpenAlexW2048400008WikidataQ57976668 ScholiaQ57976668MaRDI QIDQ4434424

José A. Vilar-Fernández, Juan M. Vilar Fernández, Mario Francisco Fernández

Publication date: 6 November 2003

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

Full work available at URL: https://doi.org/10.1081/sta-120025386

zbMATH Keywords

local polynomial fittingstrong consistencydependent data

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20)

Related Items (1)

Numerical discretization-based kernel type estimation methods for ordinary differential equation models

Cites Work

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• Approximation theorems for strongly mixing random variables
• Nonparametric regression estimation under mixing conditions
• Strong uniform convergence rates in robust nonparametric time series analysis and prediction: Kernel regression estimation from dependent observations
• Consistent regression estimation with fixed design points under dependence conditions
• Fixed design regression for time series: Asymptotic normality
• Nonparametric function estimation involving time series
• Consistent nonparametric regression. Discussion
• Recursive estimation of regression functions by local polynomial fitting
• Functional estimation for time series: Uniform convergence properties
• Local polynomial estimators of the volatility function in nonparametric autoregression
• Distribution-free strong consistency for nonparametric kernel regression involving nonlinear time series
• Kernel density estimation for random fields. (Density estimation for random fields)
• Multivariate regression estimation: Local polynomial fitting for time series
• Recursive local polynomial regression under dependence conditions
• Multivariate locally weighted least squares regression
• Local polynomial regression smoothers with AR-error structure.
• The functional law of the iterated logarithm for stationary strongly mixing sequences
• Local linear regression smoothers and their minimax efficiencies
• Nonparametric Estimation and Identification of Nonlinear ARCH Time Series Strong Convergence and Asymptotic Normality: Strong Convergence and Asymptotic Normality
• Robust Locally Weighted Regression and Smoothing Scatterplots
• MULTIVARIATE LOCAL POLYNOMIAL REGRESSION FOR TIME SERIES:UNIFORM STRONG CONSISTENCY AND RATES
• Local Polynomial Estimation of Regression Functions for Mixing Processes
• LOCAL POLYNOMIAL REGRESSION ESTIMATION WITH CORRELATED ERRORS
• Designs for Regression Problems with Correlated Errors III
• Convergence of stochastic processes
• Fixed-design regression for linear time series

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