Bayesian Analysis of the Seasonal Moving Average Model: A Gibbs Sampling Approach
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- Ismail M.A.
- United Arab Emirates University
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Abstract
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.
Journal
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- Ouyou toukeigaku
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Ouyou toukeigaku 32 (2), 61-75, 2003
Japanese Society of Applied Statistics
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Details 詳細情報について
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- CRID
- 1390282679418356992
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- NII Article ID
- 10011938303
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- NII Book ID
- AN00330942
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- ISSN
- 18838081
- 02850370
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- NDL BIB ID
- 6805210
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- Text Lang
- en
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed