Ensemble Kalman

Ensemble Kalman methods are a class of sequential Monte Carlo methods for filtering and smoothing in state-space models. They are particularly useful for high-dimensional systems where traditional Kalman filters are computationally infeasible. This submodule implements atomic functions for ensemble Kalman filters and smoothers, as well as utilities of covariance localization.

• Ensemble Kalman filtering
• Ensemble Rauch-Tung-Striebel smoothing
• Covariance localization

The high-level interfaces built on these functions are in cuthbert.ensemble_kalman.