An Ensemble Kalman Filter and Smoother for Satellite Data Assimilation
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- Christopher Wikle & Mevin Hooten, 2010. "A general science-based framework for dynamical spatio-temporal models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 19(3), pages 417-451, November.
- Margaret C Johnson & Brian J Reich & Josh M Gray, 2021. "Multisensor fusion of remotely sensed vegetation indices using space‐time dynamic linear models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(3), pages 793-812, June.
- Hajiha, Mohammadmahdi & Liu, Xiao & Lee, Young M. & Ramin, Moghaddass, 2022. "A physics-regularized data-driven approach for health prognostics of complex engineered systems with dependent health states," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
- Guillermo Ferreira & Jorge Mateu & Emilio Porcu, 2018. "Spatio-temporal analysis with short- and long-memory dependence: a state-space approach," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(1), pages 221-245, March.
- S. R. Johnson & S. E. Heaps & K. J. Wilson & D. J. Wilkinson, 2023. "A Bayesian spatio‐temporal model for short‐term forecasting of precipitation fields," Environmetrics, John Wiley & Sons, Ltd., vol. 34(8), December.
- Guanzhou Wei & Xiao Liu & Russell Barton, 2024. "An extended PDE‐based statistical spatio‐temporal model that suppresses the Gibbs phenomenon," Environmetrics, John Wiley & Sons, Ltd., vol. 35(2), March.
- Marcin Jurek & Matthias Katzfuss, 2023. "Scalable spatio‐temporal smoothing via hierarchical sparse Cholesky decomposition," Environmetrics, John Wiley & Sons, Ltd., vol. 34(1), February.
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