Bridging the ensemble Kalman filter and particle filters: The adaptive Gaussian mixture filter

DOI10.1007/s10596-010-9207-1zbMath1213.62151OpenAlexW2076546887MaRDI QIDQ536585

Geir Nævdal, Brice Vallès, Andreas S. Stordal, Hans Arnfinn Karlsen, Hans Julius Skaug

Publication date: 19 May 2011

Published in: Computational Geosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10596-010-9207-1

zbMATH Keywords

nonlinear filteringdata assimilation

Mathematics Subject Classification ID

Related Items (27)

Hierarchical sparse observation models and informative prior for Bayesian inference of spatially varying parameters ⋮ Understanding the Ensemble Kalman Filter ⋮ Kalman filter variants in the closed skew normal setting ⋮ A comparison of nonlinear extensions to the ensemble Kalman filter. Gaussian anamorphosis and two-step ensemble filters ⋮ Bandwidth selection in pre-smoothed particle filters ⋮ Bayesian estimation of agent-based models ⋮ Adaptive approximation of higher order posterior statistics ⋮ Evaluation of Gaussian approximations for data assimilation in reservoir models ⋮ Bayesian inversion in resin transfer molding ⋮ Bridging deep convolutional autoencoders and ensemble smoothers for improved estimation of channelized reservoirs ⋮ Iterative Bayesian inversion with Gaussian mixtures: finite sample implementation and large sample asymptotics ⋮ Second-order Accurate Ensemble Transform Particle Filters ⋮ A Defensive Marginal Particle Filtering Method for Data Assimilation ⋮ Filtering with state space localized Kalman gain ⋮ A modified randomized maximum likelihood for improved Bayesian history matching ⋮ An IMM filter defined in the linear-circular domain, application to maneuver detection with heading only ⋮ An iterative version of the adaptive Gaussian mixture filter ⋮ Ensemble smoothers for inference of hidden states and parameters in combinatorial regulatory model ⋮ Uncertainty quantification and optimal decisions ⋮ Parallel probabilistic graphical model approach for nonparametric Bayesian inference ⋮ A Hybrid Ensemble Transform Particle Filter for Nonlinear and Spatially Extended Dynamical Systems ⋮ Complex geology estimation using the iterative adaptive Gaussian mixture filter ⋮ Assessment of ordered sequential data assimilation ⋮ Bridging multipoint statistics and truncated Gaussian fields for improved estimation of channelized reservoirs with ensemble methods ⋮ Bayesian Inverse Problems and Kalman Filters ⋮ Affine-mapping based variational ensemble Kalman filter ⋮ Ensemble Kalman filter based sequential Monte Carlo sampler for sequential Bayesian inference

Uses Software

• EnKF

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Sampling the posterior: an approach to non-Gaussian data assimilation
• Sequential Monte Carlo Methods in Practice
• Curse-of-dimensionality revisited: Collapse of the particle filter in very large scale systems
• Sequential Imputations and Bayesian Missing Data Problems
• Mixture Kalman Filters
• Gaussian sum particle filtering
• Data Assimilation

This page was built for publication: Bridging the ensemble Kalman filter and particle filters: The adaptive Gaussian mixture filter