Durbin, James,   1923- <br/><br/>
Time series analysis by state space methods /  
J. Durbin and S. J. Koopman. 
 - Oxford :   Oxford University Press,   2001. 
 - xvii, 253 páginas :   tablas, gráficas ;   24 cm. 
 - Oxford statistical science series ;   24 .
<br/><br/>Incluye referencias bibliográficas (páginas 241-247) e índices. 
<br/><br/>1. Introduction -- I. The linear Gaussian state space model: 2. Local level model ; 3. Linear Gaussian state space models ; 4. Filtering, smoothing and forecasting ; 5. Initialisation of filter and smoother ; 6. Further computational aspects ; 7. Maximum likelihood estimation ; 8. Bayesian analysis ; 9. Illustrations of the use of the linear Gaussian Model -- II. Non-Gaussian and nonlinear state space models : 10. Non-Gausian and nonlinear state space models ; 11. Importance sampling ; 12. Analysis from a classical standpoint ; 13. Analysis from a Bayesian standpoint ; 14. Non-Gaussian and nonlinear illustrations. 
<br/><br/><label>ISBN: </label>0198523548 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Representación espacio-estado<br/>Procesos de Gauss<br/>Modelos estadísticos
<br/><br/><label>Dewey Class. No.: </label>519.55   / D87t