Smoothing With Couplings of Conditional Particle Filters
Author:
Affiliation:
1. Department of Statistics, Harvard University, Cambridge, MA;
2. Division of Statistics and Machine Learning, Linköping University, Linköping, Sweden;
3. Department of Information Technology, Uppsala University, Uppsala, Sweden
Funder
National Science Foundation
Publisher
Informa UK Limited
Subject
Statistics, Probability and Uncertainty,Statistics and Probability
Link
https://www.tandfonline.com/doi/pdf/10.1080/01621459.2018.1548856
Reference68 articles.
1. Odeint – Solving Ordinary Differential Equations in C++
2. Particle Markov chain Monte Carlo methods
3. Uniform ergodicity of the iterated conditional SMC and geometric ergodicity of particle Gibbs samplers
4. Time series analysis via mechanistic models
5. Smoothing algorithms for state–space models
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