ScholarGate
Asistent

Porovnať metódy

Prezrite si vybrané metódy vedľa seba; riadky, ktoré sa líšia, sú zvýraznené.

Bayesovský model priestorových chýb×Priestorová autokorelácia×
OdborPriestorová analýzaPriestorová analýza
RodinaRegression modelRegression model
Rok vzniku1988 (classical SEM); 2009 (Bayesian formulation)1950
TvorcaLeSage & Pace (Bayesian treatment); Anselin (classical SEM)P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995)
TypBayesian spatial regressionSpatial statistic / exploratory spatial data analysis
Pôvodný zdrojLeSage, 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 ↗
Ďalšie názvyBayesian SEM, Bayesian spatial-error regression, BSEM spatial econometrics, Bayesian spatially correlated error modelspatial dependence, geographic autocorrelation, spatial clustering measure, SA
Príbuzné65
ZhrnutieThe 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.Spatial autocorrelation quantifies the degree to which a variable's values at nearby locations resemble each other more (positive autocorrelation) or less (negative autocorrelation) than expected by chance. Global indices such as Moran's I summarise the pattern across the entire study area, while local variants reveal clusters and outliers at the level of individual observations.
ScholarGateDátová sada
  1. v1
  2. 2 Zdroje
  3. PUBLISHED
  1. v1
  2. 2 Zdroje
  3. PUBLISHED

Prejsť na hľadanie Stiahnuť snímky

ScholarGatePorovnať metódy: Bayesian Spatial Error Model · Spatial Autocorrelation. Získané 2026-06-15 z https://scholargate.app/sk/compare