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बेयसियन स्थानिक त्रुटि मॉडल (Bayesian SEM)×मोरन का I×
क्षेत्रस्थानिक विश्लेषणस्थानिक विश्लेषण
परिवारRegression modelRegression model
उद्भव वर्ष1988 (classical SEM); 2009 (Bayesian formulation)1950
प्रवर्तकLeSage & Pace (Bayesian treatment); Anselin (classical SEM)Patrick A. P. Moran
प्रकारBayesian spatial regressionSpatial autocorrelation statistic
मौलिक स्रोतLeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗
उपनामBayesian SEM, Bayesian spatial-error regression, BSEM spatial econometrics, Bayesian spatially correlated error modelMoran's I statistic, global Moran's I, spatial autocorrelation index, Moran index
संबंधित66
सारांशThe 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.Moran's I is the standard global statistic for detecting spatial autocorrelation: whether nearby locations tend to share similar values. The index ranges from approximately −1 (perfect dispersion) through 0 (spatial randomness) to +1 (perfect clustering), allowing researchers to test whether a geographic pattern differs from complete spatial randomness with a single, interpretable number.
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