Mixture ensemble Kalman filters

Marco Frei and Hans R. Künsch

Computational Statistics & Data Analysis, 2013, vol. 58, issue C, 127-138

Abstract: A generic algorithmic framework for nonlinear ensemble filtering based on Gaussian mixtures and fuzzy clustering techniques is introduced. The framework generalizes the ensemble Kalman filter and relaxes the assumption of a Gaussian prediction distribution. A theoretical analysis of the proposed procedure is provided, establishing strong consistency under suitable assumptions. Specific implementations are discussed and adjustments that are necessary in high-dimensional settings are proposed. A simple implementation of the filter is shown to work well in common testbeds, providing substantial gains over the ensemble Kalman filter.

Keywords: Nonlinear filtering; Data assimilation; Ensemble Kalman filter; Fuzzy clustering; Gaussian mixtures (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:58:y:2013:i:c:p:127-138

DOI: 10.1016/j.csda.2011.04.013

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