Communications for Statistical Applications and Methods

  • 제22권6호
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  • Pages.557-573
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  • 2015
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  • 2287-7843(pISSN)
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  • 2383-4757(eISSN)
한국통계학회 (The Korean Statistical Society)
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Gibbs Sampling for Double Seasonal Autoregressive Models

  • Amin, Ayman A. (Department of Mathematics, Statistics and Insurance, Munofia University) ;
  • Ismail, Mohamed A. (Department of Statistics, Faculty of Economics and Political Science, Cairo University)
  • 투고 : 2015.01.29
  • 심사 : 2015.09.23
  • 발행 : 2015.11.30
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초록

In this paper we develop a Bayesian inference for a multiplicative double seasonal autoregressive (DSAR) model by implementing a fast, easy and accurate Gibbs sampling algorithm. We apply the Gibbs sampling to approximate empirically the marginal posterior distributions after showing that the conditional posterior distribution of the model parameters and the variance are multivariate normal and inverse gamma, respectively. The proposed Bayesian methodology is illustrated using simulated examples and real-world time series data.

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참고문헌

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피인용 문헌

  1. Bayesian inference for double SARMA models pp.1532-415X, 2018, https://doi.org/10.1080/03610926.2017.1390132
  2. Bayesian identification of double seasonal autoregressive time series models pp.1532-4141, 2018, https://doi.org/10.1080/03610918.2018.1458130