Efficient Block Sampling Strategies for Sequential Monte Carlo Methods

Keywords

Markov chain Monte Carlo, Slice sampling, Computer science, Monte Carlo method, Sampling (signal processing)

References

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Cited by

• Computational Methods for a Class of Network ModelsJunshan Wang, Ajay Jasra, Maria De Iorio — 2013
• Particle Filtering and Smoothing: Fifteen years laterArnaud Doucet, Adam M. Johansen — 2008
• State space modelling of extreme values with particle filtersDavid Wyncoll — 2009
• A new particle filtering algorithm for multiple target tracking with non-linear observationsLan Jiang, Sumeetpal S. Singh, Sinan Yıldırım — 2014
• Computational intelligence sequential Monte Carlos for recursive Bayesian estimationAyub Hanif — 2013
• Maximum likelihood parameter estimation in time series models using sequential Monte CarloSinan Yıldırım — 2013
• Approximation and Search Optimization on Massive Data Bases and Data StreamsKai Zeng — 2014
• Particle move-reweighting strategies for online inferenceReinaldo Marques, Geir Storvik — 2013
• Some contributions to particle Markov chain Monte Carlo algorithmsA. Persing — 2013
• Particle Markov chain Monte Carlo methodsChristophe Andrieu, Arnaud Doucet, Roman Holenstein — 2010
• Control engineering perspective of fermentation process from zymomonas mobilis: Modeling, state estimation and controlOlga Lucía Quintero Montoya, Juan E. Nieto-Julián, Adriana Amicarelli — 2009
• Metoda filtru cząsteczkowegoKatarzyna Brzozowska‐Rup, Antoni Leon Dawidowicz — 2009
• Control based on numerical methods and recursive Bayesian estimation in a continuous alcoholic fermentation processOlga Lucía Quintero Montoya, Adriana A. Amicarelli, Gustavo Scaglia — 2009
• Uncertainty quantification in complex systems using approximate solversPhaedon‐Stelios Koutsourelakis — 2008
• State estimation in alcoholic continuous fermentation of Zymomonas mobilis using recursive Bayesian filtering: A simulation approachOlga Lucía Quintero Montoya, Adriana A. Amicarelli, Fernando di Sciascio — 2008
• Advances in computational Bayesian statistics and the approximation of Gibbs measuresJames Ridgway — 2015
• Performance Bounds for Particle Filters Using the Optimal ProposalChris Snyder, Thomas Bengtsson, Mathias Morzfeld — 2015
• Sample-based Probabilistic Estimation for Indoor Positioning and Tracking Under Ranging Uncertainty (Abtastungsbasierte probabilistische Schätzung für Indoor-Positionierung und Verfolgung unter der Unsicherheit der Entfernungsmessung)Yuan Yang — 2015
• Computation of Gaussian orthant probabilities in high dimensionJames Ridgway — 2014
• Fight sample degeneracy and impoverishment in particle filters: A review of intelligent approachesTiancheng Li, Shudong Sun, Tariq Sattar — 2013

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