ScholarGate
Assistent

Sammenlign metoder

Gennemgå dine valgte metoder side om side; rækker, der afviger, er fremhævet.

Robuste Lokale Indikatorer for Rumlig Association (Robust LISA)×Rumlig Autokorrelation×
FagområdeRumlig analyseRumlig analyse
FamilieRegression modelRegression model
Oprindelsesår1995–2000s1950
OphavspersonAnselin (LISA, 1995); robust extensions by Assuncao & Reis and subsequent spatial statisticiansP. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995)
TypeLocal spatial autocorrelation statistic (robust variant)Spatial statistic / exploratory spatial data analysis
Oprindelig kildeAnselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115. DOI ↗Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗
AliasserRobust LISA, outlier-resistant LISA, robust local spatial autocorrelation, LISA with robust weightsspatial dependence, geographic autocorrelation, spatial clustering measure, SA
Relaterede65
ResuméRobust Local Indicators of Spatial Association extend Anselin's LISA framework to handle outliers, extreme values, and spatially heterogeneous populations. By applying outlier-resistant adjustments to the spatial weights or the standardised values, Robust LISA identifies statistically significant local clusters and spatial outliers without the distortions caused by highly influential observations.Spatial 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.
ScholarGateDatasæt
  1. v1
  2. 2 Kilder
  3. PUBLISHED
  1. v1
  2. 2 Kilder
  3. PUBLISHED

Gå til søgning Hent slides

ScholarGateSammenlign metoder: Robust Local Indicators of Spatial Association · Spatial Autocorrelation. Hentet 2026-06-19 fra https://scholargate.app/da/compare