Semiparametric estimation of regression functions in autoregressive models

DOI10.1016/j.spl.2008.07.047zbMath1155.62071OpenAlexW2073342237MaRDI QIDQ1003415

De-Hui Wang, Zhuoxi Yu, Ning-Zhong Shi

Publication date: 4 March 2009

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2008.07.047

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20) Point estimation (62F10)

Related Items (6)

Nonlinear semiparametric autoregressive model with finite mixtures of scale mixtures of skew normal innovations ⋮ A semiparametric approach for modeling partially linear autoregressive model with skew normal innovations ⋮ Nonlinear semiparametric AR(1) model with skew-symmetric innovations ⋮ A semiparametric method for estimating nonlinear autoregressive model with dependent errors ⋮ Nonlinear autoregressive model with stochastic volatility innovations: semiparametric and Bayesian approach ⋮ Nonlinear autoregressive stochastic frontier model with dynamic technical inefficiency in panel data

Cites Work

• On conditional least squares estimation for stochastic processes
• Nonparametric regression with errors in variables
• Locally parametric nonparametric density estimation
• Local polynomial estimators of the volatility function in nonparametric autoregression
• Semiparametric density estimation by local \(L_ 2\)-fitting.
• Nonparametric density estimation with a parametric start
• Mixing Conditions for Markov Chains
• Kernel deconvolution of stochastic volatility models
• On extended partially linear single-index models
• Local Likelihood for non‐parametric ARCH(1) models

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