An Introduction to Sequential Monte Carlo. 1st ed. 2020

フォーマット:

電子ブック

責任表示:

by Nicolas Chopin, Omiros Papaspiliopoulos

言語:

英語

出版情報:

Cham : Springer International Publishing : Imprint: Springer, 2020

形態:

XXIV, 378 p. 60 illus : online resource

著者名:

• Chopin, Nicolas
• Papaspiliopoulos, Omiros
• SpringerLink (Online service)

シリーズ名:

Springer Series in Statistics ;

目次情報:

1 Preface
2 Introduction to state-space models
3 Beyond state-space models
4 Introduction to Markov processes
5 Feynman-Kac models: definition, properties and recursions
6 Finite state-spaces and hidden Markov models
7 Linear-Gaussian state-space models
8 Importance sampling
9 Importance resampling
10 Particle filtering
11 Convergence and stability of particle filters
12 Particle smoothing
13 Sequential quasi-Monte Carlo
14 Maximum likelihood estimation of state-space models
15 Markov chain Monte Carlo
16 Bayesian estimation of state-space models and particle MCMC
17 SMC samplers
18 SMC2, sequential inference in state-space models
19 Advanced topics and open problems

1 Preface
2 Introduction to state-space models
3 Beyond state-space models
4 Introduction to Markov processes
5 Feynman-Kac models: definition, properties and recursions
6 Finite state-spaces and hidden Markov models

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書誌ID:

IT00015827

ISBN:

9783030478452 [3030478459]      
9783030478476 [3030478475]