A Classification EM algorithm for clustering and two stochastic versions
Computational Statistics & Data Analysis - Special issue on optimization techniques in statistics
On sequential Monte Carlo sampling methods for Bayesian filtering
Statistics and Computing
Estimation of high-dimensional prior and posterior covariance matrices in Kalman filter variants
Journal of Multivariate Analysis
Editorial: The third special issue on Statistical Signal Extraction and Filtering
Computational Statistics & Data Analysis
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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.