Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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Finite Population Prediction under Multiprocess Dynamic Generalized Linear Models

  • Kim, Dal-Ho (Department of Statistics, Kyungpook National University) ;
  • Cha, Young-Joon (Department of Statistics, Andong National University) ;
  • Lee, Jae-Man (Department of Statistics, Andong National University)
  • Published : 1999.10.31
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Abstract

We consider a Bayesian forcasting method for the analysis of repeated surveys. It is assumed that the parameters of the superpopulation model at each time follow a stochastic model. We propose Bayesian prediction procedures for the finite population total under multiprocess dynamic generalized linear models. The multiprocess dynamic model offers a powerful framework for the modelling and analysis of time series which are subject to a abrupt changes in pattern. Some numerical studies are provided to illustrate the behavior of the proposed predictors.

Keywords

References

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