The scope of the Kalman filter for spatio‐temporal applications in environmental science

Author:

Rougier Jonathan1ORCID,Brady Aoibheann23ORCID,Bamber Jonathan2,Chuter Stephen2,Royston Sam2,Vishwakarma Bramha Dutt245,Westaway Richard2,Ziegler Yann2

Affiliation:

1. School of Mathematics University of Bristol Bristol UK

2. School of Geographical Sciences University of Bristol Bristol UK

3. Cervest London UK

4. Interdisciplinary Centre for Water Research Indian Institute of Science Bangalore India

5. Centre for Earth Science Indian Institute of Science Bangalore India

Funder

H2020 European Research Council

Publisher

Wiley

Subject

Ecological Modeling,Statistics and Probability

Reference36 articles.

1. Arthur D. &Vassilvitskii S.(2007).k‐means++: The advantages of careful seeding.Proceedings of the 18th ACM‐SIAM Symposium on Discrete Algorithms 1027–1035.

2. Harnessing the GPS Data Explosion for Interdisciplinary Science

3. Latent Gaussian random field mixture models

4. The change of support problem through the INLA approach;Cameletti M.;Statistica & Applicazioni,2013

5. Spatio-temporal modeling of particulate matter concentration through the SPDE approach

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