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Efficient Estimation For Periodic Autoregressive Coefficients Via Residuals

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  • L. Tang
  • Q. Shao

Abstract

type="main" xml:id="jtsa12070-abs-0001"> A two-step estimation method is proposed for periodic autoregressive parameters via residuals when the observations contain trend and periodic autoregressive time series. The oracle efficiency of the proposed Yule–Walker-type estimator is established. The performance is illustrated by simulation studies and real data analysis.

Suggested Citation

  • L. Tang & Q. Shao, 2014. "Efficient Estimation For Periodic Autoregressive Coefficients Via Residuals," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(4), pages 378-389, July.
    • Handle: RePEc:bla:jtsera:v:35:y:2014:i:4:p:378-389
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    File URL: http://hdl.handle.net/10.1111/jtsa.12070
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    References listed on IDEAS

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    1. Paul L. Anderson & Mark M. Meerschaert, 2005. "Parameter Estimation for Periodically Stationary Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(4), pages 489-518, July.
    2. Qiu, D. & Shao, Q. & Yang, L., 2013. "Efficient inference for autoregressive coefficients in the presence of trends," Journal of Multivariate Analysis, Elsevier, vol. 114(C), pages 40-53.
    3. Parzen, Emanuel & Pagano, Marcello, 1979. "An approach to modeling seasonally stationary time series," Journal of Econometrics, Elsevier, vol. 9(1-2), pages 137-153, January.
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    5. Song, Qiongxia & Yang, Lijian, 2010. "Oracally efficient spline smoothing of nonlinear additive autoregression models with simultaneous confidence band," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 2008-2025, October.
    6. Q. Shao & L. J. Yang, 2011. "Autoregressive coefficient estimation in nonparametric analysis," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(6), pages 587-597, November.
    7. repec:bla:jtsera:v:25:y:2004:3:p:359-372 is not listed on IDEAS
    8. Jianhua Z. Huang & Lijian Yang, 2004. "Identification of non‐linear additive autoregressive models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(2), pages 463-477, May.
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