A Guided Sequential Monte Carlo Method for the Assimilation of Data into Stochastic Dynamical Systems

DOI10.1007/978-3-0348-0451-6_10zbMath1314.37059OpenAlexW35918681MaRDI QIDQ5253368

Sebastian Reich

Publication date: 5 June 2015

Published in: Springer Proceedings in Mathematics & Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-0348-0451-6_10

Mathematics Subject Classification ID

Generation, random and stochastic difference and differential equations (37H10) Time series analysis of dynamical systems (37M10)

Related Items (4)

Birth–death dynamics for sampling: global convergence, approximations and their asymptotics ⋮ On coupling particle filter trajectories ⋮ p-kernel Stein variational gradient descent for data assimilation and history matching ⋮ Sequential Monte Carlo with transformations

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