Backward Importance Sampling for Online Estimation of State Space Models-Reference-Cited by-同舟云学术

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Backward Importance Sampling for Online Estimation of State Space Models

Published:2023-03-17 Issue:4 Volume:32 Page:1447-1460
ISSN:1061-8600
Container-title:Journal of Computational and Graphical Statistics
language:en
Short-container-title:Journal of Computational and Graphical Statistics

Author:

Martin Alice¹,Étienne Marie-Pierre²,Gloaguen Pierre³,Le Corff Sylvain⁴^ORCID,Olsson Jimmy⁵^ORCID

Affiliation:

1. École Polytechnique, et Samovar, Télécom SudParis, Institut Polytechnique de Paris, Palaiseau, France

2. Agrocampus Ouest, CNRS, IRMAR - UMR 6625, Rennes, France

3. Université Paris-Saclay, AgroParisTech, INRAE, UMR MIA Paris-Saclay, Palaiseau, France

4. LPSM, Sorbonne Université, UMR CNRS 8001, Paris, France

5. Department of Mathematics, KTH Royal Institute of Technology, Stockholm, Sweden

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Discrete Mathematics and Combinatorics,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/10618600.2023.2174125

Reference51 articles.

1. Closed-form likelihood expansions for multivariate diffusions

2. Unbiased simulation of stochastic differential equations using parametrix expansions

3. The pseudo-marginal approach for efficient Monte Carlo computations

4. Retrospective exact simulation of diffusion sample paths with applications

5. Exact and computationally efficient likelihood-based estimation for discretely observed diffusion processes (with discussion)

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