Bayesian methodsBayesian / computational

Spatial Kalman Filter

The spatial Kalman filter applies classical Kalman filtering to spatio-temporal state-space models, treating a spatially distributed latent field as the hidden state that evolves over time. At each time step, the filter recursively predicts the spatial field forward and then updates the prediction with new spatial observations, producing optimal linear estimates of the field and its uncertainty across all locations.

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Sources

  1. Cressie, N. & Wikle, C. K. (2011). Statistics for Spatio-Temporal Data. Wiley. ISBN: 978-0-471-69274-4
  2. Kalman, R. E. (1960). A new approach to linear filtering and prediction problems. Journal of Basic Engineering, 82(1), 35-45. DOI: 10.1115/1.3662552

Related methods

ScholarGateSpatial Kalman Filter (Spatial Kalman Filter for Spatio-Temporal State-Space Models). Retrieved 2026-06-04 from https://scholargate.app/en/bayesian/spatial-kalman-filter