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Локални индикатори за пространствена асоциация (LISA)×Географски претеглена регресия (GWR)×
ОбластПространствен анализПространствен анализ
СемействоRegression modelRegression model
Година на възникване19952002
СъздателLuc AnselinFotheringham, Brunsdon & Charlton
ТипLocal spatial statisticLocal spatial regression
Основополагащ източникAnselin, L. (1995). Local Indicators of Spatial Association — LISA. Geographical Analysis, 27(2), 93–115. DOI ↗Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
Други названияLISA, local spatial autocorrelation statistics, local Moran's I, Anselin LISAGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
Свързани65
РезюмеLISA, introduced by Luc Anselin in 1995, decomposes a global spatial autocorrelation index into a location-specific statistic for every observation. It identifies where statistically significant spatial clusters and outliers occur on a map, enabling researchers to move beyond a single global summary and pinpoint the geographic sources of spatial dependence.Geographically Weighted Regression is a local regression method, introduced by Fotheringham, Brunsdon and Charlton (2002), that allows the regression coefficients to vary across space. Instead of one global equation, it fits a separate set of coefficients at every location, capturing spatial heterogeneity in the relationships.
ScholarGateНабор от данни
  1. v1
  2. 2 Източници
  3. PUBLISHED
  1. v1
  2. 1 Източници
  3. PUBLISHED

Към търсенето Изтегляне на слайдове

ScholarGateСравнение на методи: Local Indicators of Spatial Association · Geographically Weighted Regression. Извлечено на 2026-06-20 от https://scholargate.app/bg/compare