Regression modelGIS / spatial

Bajezijanska geografski ponderisana regresija (BGWR)

Bajezijanska geografski ponderisana regresija kombinuje okvir prostorno promenljivih koeficijenata GWR-a sa Bajezijanskim zaključivanjem, postavljajući Gausovske procesne priore na lokalno promenljive regresione koeficijente. Ovo daje pune posteriorne distribucije za svaki koeficijent na svakoj lokaciji, pružajući principijelnu kvantifikaciju nesigurnosti umesto samo tačkastih procena.

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Izvori

  1. Finley, A. O. (2011). Comparing spatially-varying coefficients models for analysis of ecological data with non-stationary and anisotropic residual dependence. Methods in Ecology and Evolution, 2(2), 143-154. DOI: 10.1111/j.2041-210X.2010.00060.x
  2. Wheeler, D., & Calder, C. (2007). An assessment of coefficient accuracy in linear regression models with spatially varying coefficients. Journal of Geographical Systems, 9(2), 145-166. DOI: 10.1007/s10109-006-0040-y

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Bayesian Geographically Weighted Regression. ScholarGate. https://scholargate.app/sr/spatial-analysis/bayesian-geographically-weighted-regression

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Citirana u

ScholarGateBayesian Geographically Weighted Regression (Bayesian Geographically Weighted Regression). Preuzeto 2026-06-15 sa https://scholargate.app/sr/spatial-analysis/bayesian-geographically-weighted-regression · Skup podataka: https://doi.org/10.5281/zenodo.20539026