A Hybrid Ensemble Transform Particle Filter for Nonlinear and Spatially Extended Dynamical Systems

DOI10.1137/15M1040967zbMath1343.65009arXiv1509.06669OpenAlexW2963729846MaRDI QIDQ5741193

Maria Reinhardt, Nawinda Chustagulprom, Sebastian Reich

Publication date: 22 July 2016

Published in: SIAM/ASA Journal on Uncertainty Quantification (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1509.06669

zbMATH Keywords

predictiondynamical systemsMonte Carlo methodlocalizationBayesian inferenceparticle filterensemble Kalman filtersequential data assimilation

Mathematics Subject Classification ID

Related Items (8)

Sequential ensemble transform for Bayesian inverse problems ⋮ A comparison of nonlinear extensions to the ensemble Kalman filter. Gaussian anamorphosis and two-step ensemble filters ⋮ Second-order Accurate Ensemble Transform Particle Filters ⋮ A Defensive Marginal Particle Filtering Method for Data Assimilation ⋮ Ensemble Transform Algorithms for Nonlinear Smoothing Problems ⋮ Discrete gradients for computational Bayesian inference ⋮ Data assimilation: The Schrödinger perspective ⋮ Transform-based particle filtering for elliptic Bayesian inverse problems

Uses Software

• EnKF

Cites Work

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• Bridging the ensemble Kalman and particle filters
• Curse-of-dimensionality revisited: Collapse of the particle filter in very large scale systems
• Deterministic Nonperiodic Flow
• Probabilistic Forecasting and Bayesian Data Assimilation
• Data Assimilation
• Data Assimilation

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