Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Bayesian Prediction under Dynamic Generalized Linear Models in Finite Population Sampling

  • Dal Ho Kim (Department of Statistics, Kyungpook National University, Taegu, 702-701, Korea) ;
  • Sang Gil Kang (Department of Statistics, Kyungpook National University, Teagu, 702-701, Korea)
  • Published : 1997.12.01
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Abstract

In this paper, we consider a Bayesian forecasting 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 dynamic generalized linear models. Some numerical studies are provided to illustrate the behavior of the proposed predictors.

Keywords

References

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