A Defensive Marginal Particle Filtering Method for Data Assimilation

DOI10.1137/19M1237430zbMath1448.62138arXiv1810.08791OpenAlexW3081372062MaRDI QIDQ5119644

Linjun Lu, Jinglai Li, Linjie Wen, Jiangqi Wu

Publication date: 31 August 2020

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

Full work available at URL: https://arxiv.org/abs/1810.08791

zbMATH Keywords

data assimilationparticle filterensemble Kalman filtermultiple importance samplingdefensive importance samplingmarginal particle filter

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Bayesian inference (62F15) Monte Carlo methods (65C05) Statistical aspects of big data and data science (62R07)

Related Items

Ensemble Kalman filter based sequential Monte Carlo sampler for sequential Bayesian inference

Uses Software

• EnKF

Cites Work

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