Non-linear data assimilation via trust region optimization

DOI10.1007/s40314-019-0901-xzbMath1438.62152OpenAlexW2947516881MaRDI QIDQ2322777

Elias D. Nino Ruiz

Publication date: 5 September 2019

Published in: Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s40314-019-0901-x

zbMATH Keywords

data assimilationensemble Kalman filternon-linear observation operatortrust region framework

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Inference from stochastic processes and prediction (62M20) Stochastic approximation (62L20) Optimality conditions for problems involving randomness (49K45)

Uses Software

• EnKF

Cites Work

• A prior-free framework of coherent inference and its derivation of simple shrinkage estimators
• An example of numerical nonconvergence of a variable-metric method
• The BFGS method with exact line searches fails for non-convex objective functions
• Nonlinear data assimilation
• Testing for chaos in deterministic systems with noise
• Introduction to Derivative-Free Optimization
• Trust Region Methods
• An Ensemble Kalman Filter Implementation Based on Modified Cholesky Decomposition for Inverse Covariance Matrix Estimation
• Global Convergence of General Derivative-Free Trust-Region Algorithms to First- and Second-Order Critical Points
• An efficient implementation of the ensemble Kalman filter based on an iterative Sherman-Morrison formula

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