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Fixed Rank Filtering For Spatio-Temporal Data, Noel Cressie, Tao Shi, Emily L. Kang
Fixed Rank Filtering For Spatio-Temporal Data, Noel Cressie, Tao Shi, Emily L. Kang
Professor Noel Cressie
Datasets from remote-sensing platforms and sensor networks are often spatial, temporal, and very large. Processing massive amounts of data to provide current estimates of the (hidden) state from current and past data is challenging, even for the Kalman filter. A large number of spatial locations observed through time can quickly lead to an overwhelmingly high-dimensional statistical model. Dimension reduction without sacrificing complexity is our goal in this article. We demonstrate how a Spatio-Temporal Random Effects (STRE) component of a statistical model reduces the problem to one of fixed dimension with a very fast statistical solution, a methodology we call Fixed …