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

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

  1. Journal of the Royal Statistical Society, Series B v.35 A Stochastic Model for Repeated Surveys Blight, B.J.N.;Scott, A.J.
  2. Communication in Statistics-Computation and Simulation v.17 Finite Population Prediction under Dynamic Generalized Linear Models Bolfarine, H.
  3. Prediction Theory for Finite Populations Bolfarine, H.;Zacks, S.
  4. Journal of the Royal Statistical Society, Series B v.31 Subjective Bayesian Models in Sampling Finite Populations Ericson, W.A.
  5. Journal of the Royal Statistical Society, Series B v.38 Bayesian Forecasting Harrison, P.J.;Stevens, C.F.
  6. Statistics and Probability Letters v.5 A Kalman Filter Model for Single and Two-stage Repeated Surveys Rodrigues, J.;Bolfarine, H.
  7. Journal of the American Statistical Association v.69 Analysis of Repeated Surveys Using Time Series Methods Scott, A.J.;Smith, A.F.M.
  8. Journal of the American Statistical Association v.80 Dynamic Generalized Linear Models and Bayesian Forecasting West, M.;Harrison, P.J.;Migon, H.S.