Bayesian Spatial Lag Model
The Bayesian Spatial Lag Model (BSLM) extends the classical spatial autoregressive (SAR) regression by placing prior distributions over all parameters and recovering full posterior distributions via MCMC sampling. It explicitly accounts for spatial dependence — the outcome in one location is partly driven by outcomes in neighboring locations — and yields uncertainty-quantified estimates of both regression coefficients and the spatial autocorrelation parameter rho.
Source record
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- LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. · ISBN 978-1420064247
- LeSage, J. P. (1997). Bayesian Estimation of Spatial Autoregressive Models. International Regional Science Review, 20(1-2), 113-129. · DOI 10.1177/016001769702000107
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