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Regression modelGIS / spatial

Bayesiansk model for rumlig lag

Den Bayesianske model for rumlig lag (BSLM) udvider den klassiske rumlige autoregressive (SAR) regression ved at placere prior-fordelinger over alle parametre og udlede fulde posterior-fordelinger via MCMC-sampling. Den tager eksplicit højde for rumlig afhængighed – udfaldet ét sted påvirkes delvist af udfaldene i naboområder – og giver usikkerhedskvantificerede estimater af både regressionskoefficienter og den rumlige autokorrelationsparameter rho.

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Kilder

  1. LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247
  2. LeSage, J. P. (1997). Bayesian Estimation of Spatial Autoregressive Models. International Regional Science Review, 20(1-2), 113-129. DOI: 10.1177/016001769702000107

Sådan citerer du denne side

ScholarGate. (2026, June 3). Bayesian Spatial Autoregressive Lag Model. ScholarGate. https://scholargate.app/da/spatial-analysis/bayesian-spatial-lag-model

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ScholarGateBayesian Spatial Lag Model (Bayesian Spatial Autoregressive Lag Model). Hentet 2026-06-15 fra https://scholargate.app/da/spatial-analysis/bayesian-spatial-lag-model · Datasæt: https://doi.org/10.5281/zenodo.20539026