A portmanteau test for smooth transition autoregressive models

Qiang XIA, Zhiqiang ZHANG, Wai Keung LI

Research output: Contribution to journalArticlespeer-review


This article investigates a portmanteau test statistic for checking model adequacy of smooth transition autoregressive (STAR) models. The asymptotic distribution of residual autocorrelations and the least-squares estimators are also derived. Hence, the correct asymptotic standard errors for residual autocorrelations are also obtained facilitating model diagnostic checking. Through the graphical display of the simulation results concerning the size and power, for commonly used nominal sizes (≤ 0.1), the portmanteau test appears to be more advantageous than the Lagrange multiplier tests in checking serial independence for the errors of STAR models. Copyright © 2019 John Wiley & Sons Ltd.
Original languageEnglish
Pages (from-to)722-730
JournalJournal of Time Series Analysis
Issue number5
Early online dateDec 2019
Publication statusPublished - Sept 2020


Xia, Q., Zhang, Z., & Li, W. K. (2020). A portmanteau test for smooth transition autoregressive models. Journal of Time Series Analysis, 41(5), 722-730. doi: 10.1111/jtsa.12512


  • STAR models
  • Portmanteau test
  • Nonlinear time series
  • Least-squares method


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