Ensemble Kalman filtering with shrinkage regression techniques

DOI10.1007/s10596-010-9196-0zbMath1213.62149OpenAlexW1978291220MaRDI QIDQ536583

Henning Omre, Jon Sætrom

Publication date: 19 May 2011

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

Full work available at URL: https://doi.org/10.1007/s10596-010-9196-0

zbMATH Keywords

cross-validationmodel overfitting

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Ridge regression; shrinkage estimators (Lasso) (62J07)

Related Items

Kalman filter variants in the closed skew normal setting ⋮ Coupling Techniques for Nonlinear Ensemble Filtering ⋮ Perturbations and projections of Kalman-Bucy semigroups ⋮ Ensemble Kalman Methods for High-Dimensional Hierarchical Dynamic Space-Time Models ⋮ Ensemble Kalman filtering for non-linear likelihood models using kernel-shrinkage regression techniques ⋮ Ensemble-based seismic and production data assimilation using selection Kalman model ⋮ Uncertainty Quantification in the Ensemble Kalman Filter

Uses Software

• EnKF
• rda
• ElemStatLearn

Cites Work

• A well-conditioned estimator for large-dimensional covariance matrices
• Fisher lecture: Dimension reduction in regression
• Estimation of high-dimensional prior and posterior covariance matrices in Kalman filter vari\-ants
• Principal component analysis.
• Efficient quadratic regularization for expression arrays
• The Estimation of Prediction Error
• Data Assimilation
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