Linear approximation of the threshold autoregressive model: an application to order estimation

DOI10.1007/s10260-022-00638-1OpenAlexW4280562238MaRDI QIDQ6163484

Francesco Giordano, Cosimo Damiano Vitale, Marcella Niglio

Publication date: 26 June 2023

Published in: Statistical Methods and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10260-022-00638-1

zbMATH Keywords

linear approximationthreshold modelAIC\(L^2\) norm

Mathematics Subject Classification ID

Statistics (62-XX) Numerical analysis (65-XX)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Estimating linear representations of nonlinear processes
• Bilinear Markovian representation and bilinear models
• Some asymptotic theory for the bootstrap
• Time series: theory and methods.
• Strict stationarity of generalized autoregressive processes
• Information criteria: how do they behave in different models?
• Moments of Markov switching models
• Consistency and limiting distribution of the least squares estimator of a threshold autoregressive model
• Improved model selection criteria for SETAR time series models
• Information criteria for nonlinear time series models
• Cross‐validation Criteria for Setar Model Selection
• Model Selection in Threshold Models
• Selecting nonlinear time series models using information criteria
• Statistical Inference about Markov Chains
• A threshold AR(1) model
• Linear System Identification in a Nonlinear Setting: Nonparametric Analysis of the Nonlinear Distortions and Their Impact on the Best Linear Approximation
• ON MARKOV-SWITCHING ARMA PROCESSES—STATIONARITY, EXISTENCE OF MOMENTS, AND GEOMETRIC ERGODICITY
• On the use of the deterministic Lyapunov function for the ergodicity of stochastic difference equations
• A note on the corrected Akaike information criterion for threshold autoregressive models
• Selection of the order of an autoregressive model by Akaike's information criterion
• A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle
• Testing and Modeling Threshold Autoregressive Processes
• Bootstrap order selection for SETAR models
• A new look at the statistical model identification

This page was built for publication: Linear approximation of the threshold autoregressive model: an application to order estimation