A SIMPLE VARIABLE SELECTION TECHNIQUE FOR NONLINEAR MODELS

DOI10.1081/STA-100104360zbMath1008.62620OpenAlexW2080310097MaRDI QIDQ4540654

Timo Teräsvirta, Rolf Tschernig, Gianluigi Rech

Publication date: 28 July 2002

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

Full work available at URL: https://doi.org/10.1081/sta-100104360

Mathematics Subject Classification ID

General nonlinear regression (62J02) Nonparametric inference (62G99)

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A multiple regime smooth transition heterogeneous autoregressive model for long memory and asymmetries ⋮ A practical approach to parameter estimation applied to model predicting heart rate regulation ⋮ A Simple Specification Procedure for the Transition Function in Persistent Nonlinear Time Series Models ⋮ \(\ell_1\)-regularization of high-dimensional time-series models with non-Gaussian and heteroskedastic errors ⋮ Testing the Granger Noncausality Hypothesis in Stationary Nonlinear Models of Unknown Functional Form ⋮ Identification of Non-Linear Additive Autoregressive Models

Cites Work

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• Modeling by shortest data description
• Fitting autoregressive models for prediction
• Nonparametric Lag Selection for Time Series
• Nonparametric Identification of Nonlinear Time Series: Selecting Significant Lags
• Order Choice in Nonlinear Autoregressive Models
• Multivariate Bandwidth Selection for Local Linear Regression
• A new look at the statistical model identification

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