Bayesian Analysis of the Seasonal Moving Average Model : A Gibbs Sampling Approach

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概要

• 論文の詳細を見る

• This paper develops a Bayesian analysis for the multiplicative seasonal moving average model by implementing a fast, easy and accurate Gibbs sampling algorithm. The proposed algorithm does not involve any Metropolis-Hastings generation but is generated from normal and inverse gamma distributions. The problem of forecasting multiple future observations is considered. The proposed algorithm is illustrated using a simulated example and airline data. Unlike the classical approach, by using the airline data, the proposed algorithm is easily used to test the significance of the interaction parameter.

• 応用統計学会の論文
• 2003-12-15

著者

• Ismail Mohamed

  United Arab Emirates University

関連論文

• Bayesian Analysis of the Seasonal Moving Average Model : A Gibbs Sampling Approach

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