Porównaj metody
Przeglądaj wybrane metody obok siebie; wiersze, które się różnią, są wyróżnione.
| Bayesowski Model Durba Spatialnego× | Model błędu przestrzennego (SEM)× | |
|---|---|---|
| Dziedzina | Analiza przestrzenna | Analiza przestrzenna |
| Rodzina | Regression model | Regression model |
| Rok powstania≠ | 2009 | 1988 |
| Twórca≠ | LeSage & Pace | Anselin |
| Typ≠ | Bayesian spatial regression | Spatial regression (spatially autocorrelated errors) |
| Źródło pierwotne≠ | LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247 | Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic. DOI ↗ |
| Inne nazwy | Bayesian SDM, Bayesian spatial lag-X model, Bayesian SDM with spatially lagged covariates, BSDM | SEM, spatial error regression, spatial autoregressive error model, Uzamsal Hata Modeli (SEM / Spatial Error) |
| Pokrewne≠ | 6 | 5 |
| Podsumowanie≠ | The Bayesian Spatial Durbin Model (BSDM) estimates a spatial regression that simultaneously includes a spatially lagged outcome variable and spatially lagged covariates, using Bayesian inference with Markov Chain Monte Carlo sampling. It captures both endogenous and exogenous spatial spillovers while providing full posterior distributions for all parameters, quantifying uncertainty beyond what classical maximum-likelihood estimation offers. | The Spatial Error Model, developed within Anselin's spatial econometrics framework (1988), is a regression model that assumes spatial dependence enters through the error term: the disturbances of neighbouring units are correlated. It is used when unobserved shared factors make the errors of nearby observations move together, and it is estimated by maximum likelihood or GMM rather than ordinary least squares. |
| ScholarGateZbiór danych ↗ |
|
|