On-line change-point detection (for state space models) using multi-process Kalman filters

Linear Algebra and Its Applications

Volumn 284, Issue 1-3, 1998, Pages 125-135

  Daumer, Martin ^a   Falk, Markus ^a  

^a TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0043080076     PISSN: 00243795     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0024-3795(98)10132-5     Document Type: Article

References (6)

1. A.F.M. Smith, M. West, Monitoring renal transplants: An application of the multi-process Kalman filter, Biometrics 39 (1983) 867-878.
2. J. Whittaker, Frühwirth-Schnatter, A dynamic change-point model for detecting the onset of the growth in bacteriological infections, Appl. Statist. 43 (4) (1994).
3. M. West, P.J. Harrison, Bayesian Forecasting and Dynamical Models, Springer, New York, 1989.
4. G. Kitagawa, Monte Carlo smoother for non-gaussian non-linear state space models, J. Comput. Graphical Stat. 5 (1996) 1-25.
5. G. Kitagawa, N. Matsumoto, Detection of coseismic changes of underground water level, Jasa 91 (1996) 521-528.
6. S. Kim, N. Shephard, S. Chib, Stochastic volatility: Likelihood inference and comparison with arch models, Technical Report, 1996.