Monte Carlo Kalman filter and smoothing for multivariate discrete state space models

Canadian Journal of Statistics

Volumn 28, Issue 3, 2000, Pages 641-652

  Song, Peter Xue Kun ^a  

^a YORK UNIVERSITY   (Canada)

Author keywords

Binomial time series; Kalman filter; Monte Carlo; Smoothing; State space model

Indexed keywords

EID: 0034361312     PISSN: 03195724     EISSN: None     Source Type: Journal    
DOI: 10.2307/3315971     Document Type: Article

References (15)

1. P. J. Brockwell & R. A. Davis (1987). Time Series: Theory and Methods. Springer-Verlag, New York.
2. B. P. Carlin & N. G. Polson (1992). Monte Carlo Bayesian methods for discrete regression models and categorical time series. Bayesian Statistics, 4, 577-586.
3. B. P. Carlin, N. G. Polson & D. S. Stoffer (1992). A Monte Carlo approach to nonnormal and nonlinear state-space modeling. Journal of the American Statistical Association, 87, 493-500.
4. C. Czado (1997). Multivariate probit analysis of binary time series data with missing responses. Unpublished manuscript.
5. L. Fahrmeir (1992). Posterior mode estimation by extended Kalman filtering for multivariate dynamic generalized linear models. Journal of the American Statistical Association, 87, 501-509.
6. L. Fahrmeir & G. Tutz (1994). Multivariate Statistical Modelling Based on Generalized Linear Models. Springer-Verlag, New York.
7. J. Geweke (1991). Efficient simulation from the multivariate normal and student-t distributions subject to linear constraints. Computing Science and Statistics, Proceedings of the 23rd Symposium on the Interface, Seattle, WA, pp. 571-578.
8. A. C. Harvey (1981). Time Series Models. Allan, Oxford.
9. B. Jørgensen, S. Lundbye-Christensen, P. X.-K. Song & L. Sun (1996). State-space models for multivariate longitudinal data of mixed types. The Canadian Journal of Statistics, 24, 385-402.
10. B. Jørgensen, S. Lundbye-Christensen, P. X.-K. Song & L. Sun (1999). A state-space model for multivariate longitudinal count data. Biometrika, 86, 169-181.
11. G. Kitagawa (1987). Non-Gaussian state-space modeling of nonstationary time series (with discussion). Journal of the American Statistical Association, 82, 1032-1063.
12. U. V. Naik-Nimbalkar & M. R. Rajarshi (1995). Filtering and smoothing via estimating functions. Journal of the American Statistical Association, 90, 301-306.
13. C. P. Robert (1995). Simulate of truncated normal variables. Statistics and Computing, 5, 121-125.
14. D. S. Stoffer, M. S. Scher, G. A. Richardson, N. L. Day & P. A. Coble (1988). A Walsh-Fourier analysis of the effects of moderate maternal alcohol consumption on neonatal sleep-state cycling. Journal of the American Statistical Association, 83, 954-963.
15. T. A. Tanner & W. H. Wong (1987). The calculation of posterior distributions by data augmentation. Journal of the American Statistical Association, 82, 528-547.