Book contents
- Frontmatter
- Contents
- List of contributors
- Preface
- 1 Inference and estimation in probabilistic time series models
- I Monte Carlo
- II Deterministic approximations
- III Switching models
- IV Multi-object models
- 11 Approximate likelihood estimation of static parameters in multi-target models
- 12 Sequential inference for dynamically evolving groups of objects
- 13 Non-commutative harmonic analysis in multi-object tracking
- V Nonparametric models
- VI Agent-based models
- Index
- Plate section
- References
11 - Approximate likelihood estimation of static parameters in multi-target models
from IV - Multi-object models
Published online by Cambridge University Press: 07 September 2011
Book contents
- Frontmatter
- Contents
- List of contributors
- Preface
- 1 Inference and estimation in probabilistic time series models
- I Monte Carlo
- II Deterministic approximations
- III Switching models
- IV Multi-object models
- 11 Approximate likelihood estimation of static parameters in multi-target models
- 12 Sequential inference for dynamically evolving groups of objects
- 13 Non-commutative harmonic analysis in multi-object tracking
- V Nonparametric models
- VI Agent-based models
- Index
- Plate section
- References
Summary
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- Bayesian Time Series Models , pp. 225 - 244Publisher: Cambridge University PressPrint publication year: 2011
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