Adaptive Estimation of Periodic First-Order Threshold Autoregressive Model

作者：Bentarzi M^*; Djeddou L

来源：Communications in Statistics - Simulation and Computation, 2014, 43(7): 1611-1630.

DOI：10.1080/03610918.2012.740123

• Adaptive estimation
• Local Asymptotic Normality property
• Periodic Self-Exciting
• Periodically correlated process
• Threshold Autoregressive model

This paper focuses on the adaptive estimation problem of a Periodic Self-Exciting Threshold Autoregressive (PSETAR) model. The adapted sufficient conditions of Swensen (1985) to our model, are verified and then explored to establish the Local Asymptotic Normality (LAN), the Local Asymptotic Quadratic (LAQ) and the Local Asymptotic properties satisfied by its central sequence. Using these results, we construct adaptive estimators for the parameter model where the innovation density is unspecified but symmetric, while satisfying only some general conditions. The performances of these adaptive estimations are shown via simulation studies and an application on the modeling of the Fraser River data.

• 出版日期2014