Journal of the Korean Statistical Society

The Korean Statistical Society (한국통계학회)
권호 표지

Multiprocess Dynamic Poisson Mode1s: The Covariates Case

  • Published : 1998.09.01
Download PDF
⟨ Previous Next ⟩

Abstract

We propose a multiprocess dynamic Poisson model for the analysis of Poisson process with the covariates. The algorithm for the recursive estimation of the parameter vector modeling time-varying effects of covariates is suggested. Also the algorithm for forecasting of numbers of events at the next time point based on the information gathered until the current time is suggested.

Keywords

References

  1. Communication in Statistics A: Theory and Methods v.17 Estimation in the Multiprocedd Dynamic Generalized Linear Model Bolstad, W. M.
  2. Journal of the American Ststistical Association v.90 The Multiprocess Dynamic Poisson Model Bolstad, W. M.
  3. Biometrika v.79 no.1 A Dynamic approach to the Ststisstical Anslusis of Point Processes Gamerman, D.
  4. Operations Research Quarterly v.22 A Bayesian approach to Short-Term Forecasting Harrison, P. J.;Stevens, C. F.
  5. Journal of the Royal Ststistical society B v.38 Bayesian Forecasting(with discussions) Harrison, P. .J.;Stevens, C. F.
  6. Journal of the Royal Ststistical Society A v.149 The Effects of Seat Belt Legislation of Road Casualties: A Case study in Time Seies Modelling Harvey, A. C.;Durbin, J.k
  7. Bayesian Forecasting and Dynamic Models West, M.;Harrison, P. J.
  8. Journal of the American Statistical Association v.80 Dymamic Generalized Linear Models and Bayesian Forecasting Weat, M.;Harrison, P. J.;Migon, H. S.