Journal of applied mathematics & informatics

The Korean Society for Computational and Applied Mathematics (한국전산응용수학회)
권호 표지

BAYESIAN MODEL SELECTION IN REGRESSION MODEL WITH AUTOREGRESSIVE ERRORS

  • Chung, Youn-Shik (Department of Statistics, Pusan National University) ;
  • Sohn, Keon-Tae (Department of Statistics, Pusan National University) ;
  • Kim, Sung-Duk (Department of Statistics, Pusan National University) ;
  • Kim, Chan-Soo (Department of Statistics, Pusan National University)
  • Published : 2002.12.01

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Abstract

This paper considers the Bayesian analysis of the regression model wish autoregressive errors. The Bayesian approach for finding the order p of autoregressive error is proposed and the proposed method can be simplified by generalized Savage-Dicky density ratio(Verdinelli and Wasser-man, [18]). And the Markov chain Monte Carlo method(Gibbs sample, [7]) is used in order to overcome the difficulty of Bayesian computations. Final1y, several examples are used to illustrate our proposed methodology.

Keywords

References

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