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Пространствена автокорелация×Локални индикатори за пространствена асоциация (LISA)×
ОбластПространствен анализПространствен анализ
СемействоRegression modelRegression model
Година на възникване19501995
СъздателP. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995)Luc Anselin
ТипSpatial statistic / exploratory spatial data analysisLocal spatial statistic
Основополагащ източникMoran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗Anselin, L. (1995). Local Indicators of Spatial Association — LISA. Geographical Analysis, 27(2), 93–115. DOI ↗
Други названияspatial dependence, geographic autocorrelation, spatial clustering measure, SALISA, local spatial autocorrelation statistics, local Moran's I, Anselin LISA
Свързани56
РезюмеSpatial 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.LISA, 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.
ScholarGateНабор от данни
  1. v1
  2. 2 Източници
  3. PUBLISHED
  1. v1
  2. 2 Източници
  3. PUBLISHED

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ScholarGateСравнение на методи: Spatial Autocorrelation · Local Indicators of Spatial Association. Извлечено на 2026-06-19 от https://scholargate.app/bg/compare