ScholarGate
Assistent

Sammenlign metoder

Gjennomgå de valgte metodene side om side; rader som avviker, er uthevet.

Bayesiansk romlig feilmodell×Bayesiansk romlig etterslepmodell×
FagfeltRomlig analyseRomlig analyse
FamilieRegression modelRegression model
Opprinnelsesår1988 (classical SEM); 2009 (Bayesian formulation)1997
OpphavspersonLeSage & Pace (Bayesian treatment); Anselin (classical SEM)LeSage (1997); fully elaborated in LeSage & Pace (2009)
TypeBayesian spatial regressionBayesian spatial regression
Opprinnelig kildeLeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247
AliasBayesian SEM, Bayesian spatial-error regression, BSEM spatial econometrics, Bayesian spatially correlated error modelBayesian SAR model, Bayesian spatial autoregressive model, BSLM, Bayesian SLM
Relaterte65
SammendragThe 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.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.
ScholarGateDatasett
  1. v1
  2. 2 Kilder
  3. PUBLISHED
  1. v1
  2. 2 Kilder
  3. PUBLISHED

Gå til søk Download slides

ScholarGateSammenlign metoder: Bayesian Spatial Error Model · Bayesian Spatial Lag Model. Hentet 2026-06-15 fra https://scholargate.app/no/compare