Improved local polynomial estimation in time series regression

DOI10.1080/10485252.2017.1402118zbMath1415.62020OpenAlexW2770863078MaRDI QIDQ4634441

Michael H. Neumann, Juliane Geller

Publication date: 10 April 2018

Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10485252.2017.1402118

zbMATH Keywords

central limit theoremstrong mixinglocal polynomial estimationpre-whiteningtime series regression

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Central limit and other weak theorems (60F05)

Related Items (3)

Adaptive local polynomial estimations for heterogeneously variational regression functions ⋮ Regularized nonlinear regression with dependent errors and its application to a biomechanical model ⋮ Efficient estimation of nonparametric regression in the presence of dynamic heteroskedasticity

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Nonparametric transformation to white noise
• Nonparametric regression estimation with general parametric error covariance
• Weak dependence. With examples and applications.
• About the Lindeberg method for strongly mixing sequences
• Nonparametric Estimation and Identification of Nonlinear ARCH Time Series Strong Convergence and Asymptotic Normality: Strong Convergence and Asymptotic Normality
• MORE EFFICIENT ESTIMATION IN NONPARAMETRIC REGRESSION WITH NONPARAMETRIC AUTOCORRELATED ERRORS
• Quasi-likelihood Estimation in Semiparametric Models
• Local Polynomial Estimation of Regression Functions for Mixing Processes
• More Efficient Local Polynomial Estimation in Nonparametric Regression With Autocorrelated Errors
• Nonparametric Function Estimation for Clustered Data When the Predictor is Measured without/with Error
• Correlation and Marginal Longitudinal Kernel Nonparametric Regression
• A central limit theorem for triangular arrays of weakly dependent random variables, with applications in statistics

This page was built for publication: Improved local polynomial estimation in time series regression