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Bayesian time series models /
"'What's going to happen next?' Time series data hold the answers, and Bayesian methods represent the cutting edge in learning what they have to say. This ambitious book is the first unified treatment of the emerging knowledge-base in Bayesian time series techniques. Exploiting t...
| Clasificación: | Libro Electrónico |
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| Otros Autores: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cambridge, UK ; New York :
Cambridge University Press,
2011.
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| Colección: | Cambridge books online.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- 1. Inference and estimation in probabilistic time series models / David Barber, A. Taylan Cemgil and Silvia Chiappa
- I. Monte Carlo: 2. Adaptive Markov chain Monte Carlo: theory and methods / Yves Atchadé, Gersende Fort, Eric Moulines and Pierre Priouret; 3. Auxiliary particle filtering: recent developments / Nick Whiteley and Adam M. Johansen; 4. Monte Carlo probabilistic inference for diffusion processes: a methodological framework / Omiros Papaspiliopoulos
- II. Deterministic Approximations: 5. Two problems with variational expectation maximisation for time series models / Richard Eric Turner and Maneesh Sahani; 6. Approximate inference for continuous-time Markov processes / Cédric Archambeau and Manfred Opper; 7. Expectation propagation and generalised EP methods for inference in switching linear dynamical systems / Onno Zoeter and Tom Heskes; 8. Approximate inference in switching linear dynamical systems using Gaussian mixtures / David Barber
- III. Switch Models: 9. Physiological monitoring with factorial switching linear dynamical systems / John A. Quinn and Christopher K.I. Williams; 10. Analysis of changepoint models / Idris A. Eckley, Paul Fearnhead and Rebecca Killick
- IV. Multi-Object Models: 11. Approximate likelihood estimation of static parameters in multi-target models / Sumeetpal S. Singh, Nick Whiteley and Simon J. Godsill; 12. Sequential inference for dynamically evolving groups of objects / Sze Kim Pang, Simon J. Godsill, Jack Li, François Septier and Simon Hill; 13. Non-commutative harmonic analysis in multi-object tracking / Risi Kondor
- V. Nonparametric Models: 14. Markov chain Monte Carlo algorithms for Gaussian processes / Michalis K. Titsias, Magnus Rattray and Neil D. Lawrence; 15. Nonparametric hidden Markov models / Jurgen Van Gael and Zoubin Ghahramani; 16. Bayesian Gaussian process models for multi-sensor time series prediction / Michael A. Osborne, Alex Rogers, Stephen J. Roberts, Sarvapali D. Ramchurn and Nick R. Jennings
- VI. Agent-Based Models: 17. Optimal control theory and the linear Bellman equation / Hilbert J. Kappen; 18. Expectation maximisation methods for solving (PO)MDPs and optimal control problems / Marc Toussaint, Amos Storkey and Stefan Harmeling.