Method evidence record

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.

Sources recorded, not reviewed

Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Spatial Kalman Filter for Spatio-Temporal State-Space Models

Taxonomic method record · bayesian / bayesian

Cressie, N. & Wikle, C. K. (2011). Statistics for Spatio-Temporal Data. Wiley. · ISBN 978-0-471-69274-4
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

Open full method

Curated claims

Claims persisted in the evidence ledger, each with its own assessment.

No curated claims yet

This view does not invent a claim assessment when the ledger has none.

Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Taxonomic bucketDynamic Bayesian Inferencemachine-suggested · Relational suggestion, not evidence.Taxonomic bucketKalman Filtermachine-suggested · Relational suggestion, not evidence.Same method familyParticle Filtermachine-suggested · Relational suggestion, not evidence.Taxonomic bucketSequential Monte Carlomachine-suggested · Relational suggestion, not evidence.Taxonomic bucketSpatial Bayesian Inferencemachine-suggested · Relational suggestion, not evidence.Taxonomic bucketSpatial MCMCmachine-suggested · Relational suggestion, not evidence.