Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
권호 표지

Bayesian Estimation Procedure in Multiprocess Non-Linear Dynamic Normal Model

  • Published : 1996.04.01
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper we consider the multiprocess dynamic normal model with parameters having a time dependent non-linear structure. We develop and study the recursive estimation procedure for the proposed model with normality assumption. It turns out thst the proposed model has nice properties such as insensitivity to outliers and quick reaction to abrupt changes of pattern.

Keywords

References

  1. The American Statistician v.40 harrison-Stevens Forecasting and the Multiprocess Dynamic Model Bolstad, W. M.
  2. Communications in Statistics : Theory and Method v.17 Estimation in the Multiprocess Dynamic Generalized Linear Model Bolstad, W. M.
  3. Journal of the American Statistical Association v.90 The Multiprocess Dynamic Poisson Model Bolstad, W. M.
  4. Journal of the American Statistical Association v.67 Linear Dynamic Recursive Estimation from the Viewpoint of Regression Analysis Duncan, B.;Horn, S. D.
  5. Statistician v.40 Forecasting the number of AIDS cases in Brazil Gamerman, D.;Migon, H. S.
  6. Operations Research Quarterly v.22 A Bayesian Approach to Short-term Forecasting Harrison, P. J.;Stevens, C. F.
  7. Journal of the Royal Statistical Society B v.38 Bayesian Forecasting Harrison, P. J.;Stevens, C. F.
  8. IEEE Transactions on Automatic Control A Bayesian Approach to Problems in Stochastic Estimation and Control Ho, Y. C.;Lee, R. C. K.
  9. Journal of Basic Engineering A New Approach to Linear Filtering and Prediction Problems Kalman, R. E.
  10. Journal of the American Statistical Association v.82 Non-Gaussian State-Space Modeling of Nonstationary Time Series Kitagawa, W.
  11. IEEE Transaction on Automatic Control v.22 Robust Bayesian Estimation for the Linear Model and Robustifying the Kalman Filter Masreliez, C. J.;Martin, R. .D.
  12. Biometrics v.39 An Application of Multiprocess Kalman Filter to Renal Transplant Data Smith, A. F. M.;West, M.
  13. The Statistician v.32 Monitoring Kidney Transplant Patients Smith, A. F. M.;West, M.;Gordon, K.;Knapp, M.p;Trimble, I. C.
  14. Journal of the Royal Statistical Society B v.43 Robust Sequential Approximate Bayesian Estimation West, M.
  15. Journal of the Royal Statistical Society B v.48 Bayesian Model Monitoring West, M.
  16. Journal of the American Statistical Association v.81 Monitoring and Adaptation in Bayesian Forecasting Models West, M.;Harrison, P. J.
  17. Journal of the American Statistical Association v.80 Dynamic Generalized Linear Models and Bayesian Forecasting West, M.;Harrison, P. J.;Migon, H. S.
  18. Applied Statistics v.43 A Dynamic Changepoint Model for Detecting the Onset of Growth in Bacteriological Infections Whittaker, J.;Fruhwirth-Schnatter, S.