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Bayesian Spatial Error Model/Evidence
Method evidence record

Bayesian Spatial Error Model

The Bayesian Spatial Error Model (Bayesian SEM) estimates a regression in which spatially correlated disturbances are explicitly modelled through a spatial weights matrix, while all parameters — regression coefficients, spatial error autocorrelation, and error variance — receive full posterior distributions via Bayesian inference rather than point estimates.

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Source record

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

Bayesian Spatial Error Model
Taxonomic method record · regression-model / spatial-analysis
  • LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. · ISBN 978-1420064247
  • Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic Publishers. · ISBN 978-9024737291
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Curated claims

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

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Related methods

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

Taxonomic bucketBayesian Spatial Durbin Modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketBayesian Spatial Lag Modelmachine-suggested · Relational suggestion, not evidence.Same method familyGeographically Weighted Regressionmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMoran's Imachine-suggested · Relational suggestion, not evidence.Taxonomic bucketSpatial Autocorrelationmachine-suggested · Relational suggestion, not evidence.Same method familySpatial Error Modelmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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