A semiparametric method for estimating nonlinear autoregressive model with dependent errors

DOI10.1016/j.na.2011.06.016zbMath1232.62118OpenAlexW2068941272MaRDI QIDQ640165

S. J. Mortazavi, Rahman Farnoosh

Publication date: 17 October 2011

Published in: Nonlinear Analysis. Theory, Methods \& Applications. Series A: Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.na.2011.06.016

zbMATH Keywords

nonlinear autoregressive modelconditional least squares methodkernel approach

Mathematics Subject Classification ID

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Cites Work

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• Semiparametric estimation of regression functions in autoregressive models
• On conditional least squares estimation for stochastic processes
• Statistical inference in single-index and partially nonlinear models
• Linearity testing using local polynomial approximation
• Consistent model specification tests for time series econometric models
• Nonparametric regression with errors in variables
• Locally parametric nonparametric density estimation
• Nonlinear stochastic trends
• Local polynomial estimators of the volatility function in nonparametric autoregression
• Asymptotic theory of statistical inference for time series
• Semiparametric density estimation by local \(L_ 2\)-fitting.
• Efficient estimation in a semiparametric additive regression model with autoregressive errors
• NONPARAMETRIC ESTIMATORS FOR TIME SERIES
• Nonparametric Estimation and Identification of Nonlinear ARCH Time Series Strong Convergence and Asymptotic Normality: Strong Convergence and Asymptotic Normality
• ADAPTIVE SEMIPARAMETRIC ESTIMATION IN THE PRESENCE OF AUTOCORRELATION OF UNKNOWN FORM
• Mixing Conditions for Markov Chains
• SEMIPARAMETRIC TIME SERIES REGRESSION
• On extended partially linear single-index models
• Local Likelihood for non‐parametric ARCH(1) models

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