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Efficient Estimation in Smooth Threshold Autoregressive(1) Models

Article

Abstract

Verifiable conditions are given for the existence of efficient estimation in Smooth Threshold Autoregressive models of order 1. The paper establishes local asymptotic normality in the semi-parametric setting which is then used to discuss adaptive and efficient estimates of the models. It is found that the adaptation is satisfied if the error densities are symmetric. Simulation results are presented to compare the conditional least squares estimate with the adaptive and efficient estimates for the models.

AMS Subject Classification

62M10 62F10 

Keywords

Adaptive estimation efficient estimation locally asymptotically normal non-linear time series smooth threshold autoregressive stationarity 

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Copyright information

© Grace Scientific Publishing 2008

Authors and Affiliations

  1. 1.School of Mathematical and Physical SciencesUniversity of NewcastleAustralia
  2. 2.Department of Mathematics and StatisticsCurtin University of TechnologyPerthAustralia
  3. 3.Department of Mathematics and StatisticsCurtin University of TechnologyPerthAustralia

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