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AR(1) model with skew-normal innovations

Author

Listed:
  • M. Sharafi

    (Shiraz University)

  • A. R. Nematollahi

    (Shiraz University)

Abstract

In this paper, we consider an autoregressive model of order one with skew-normal innovations. We propose several methods for estimating the parameters of the model and derive the limiting distributions of the estimators. Then, we study some statistical properties and the regression behavior of the proposed model. Finally, we provide a Monte Carlo simulation study for comparing performance of estimators and consider a real time series to illustrate the applicability of the proposed model.

Suggested Citation

  • M. Sharafi & A. R. Nematollahi, 2016. "AR(1) model with skew-normal innovations," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 79(8), pages 1011-1029, November.
    • Handle: RePEc:spr:metrik:v:79:y:2016:i:8:d:10.1007_s00184-016-0587-7
    DOI: 10.1007/s00184-016-0587-7
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    References listed on IDEAS

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    1. Bondon, Pascal, 2009. "Estimation of autoregressive models with epsilon-skew-normal innovations," Journal of Multivariate Analysis, Elsevier, vol. 100(8), pages 1761-1776, September.
    2. B. Tarami & M. Pourahmadi, 2003. "Multi‐variate t Autoregressions: Innovations, Prediction Variances and Exact Likelihood Equations," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(6), pages 739-754, November.
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    Cited by:

    1. Clécio da Silva Ferreira & Gilberto A. Paula & Gustavo C. Lana, 2022. "Estimation and diagnostic for partially linear models with first-order autoregressive skew-normal errors," Computational Statistics, Springer, vol. 37(1), pages 445-468, March.
    2. T. Manouchehri & A. R. Nematollahi, 2019. "Periodic autoregressive models with closed skew-normal innovations," Computational Statistics, Springer, vol. 34(3), pages 1183-1213, September.
    3. Demetrescu, Matei & Golosnoy, Vasyl & Titova, Anna, 2020. "Bias corrections for exponentially transformed forecasts: Are they worth the effort?," International Journal of Forecasting, Elsevier, vol. 36(3), pages 761-780.

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