পদ্ধতির তুলনা করুন

	রবাস্ট গেটিস-অর্ড Gi* পরিসংখ্যান	শক্তিশালী স্থানীয় স্থানিক সংযোগ সূচক (শক্তিশালী LISA)
ক্ষেত্র	স্থানিক বিশ্লেষণ	স্থানিক বিশ্লেষণ
পরিবার	Regression model	Regression model
উদ্ভবের বছর	1992 (base); robust variants circa 2000s–2010s	1995–2000s
প্রবর্তক	Getis & Ord (base statistic); robust extensions developed in subsequent spatial statistics literature	Anselin (LISA, 1995); robust extensions by Assuncao & Reis and subsequent spatial statisticians
ধরন	Local spatial statistic	Local spatial autocorrelation statistic (robust variant)
মৌলিক উৎস	Getis, A., & Ord, J. K. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3), 189–206.	Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115.
অপর নাম	Robust Gi*, Robust local Gi star, outlier-resistant hot spot analysis, robust local spatial autocorrelation Gi*	Robust LISA, outlier-resistant LISA, robust local spatial autocorrelation, LISA with robust weights
সম্পর্কিত	5	6
সারসংক্ষেপ	The Robust Getis-Ord Gi* statistic extends the classical Gi* hot-spot measure to handle outliers in spatial data. By using robust estimators of the mean and variance — such as trimmed means, medians, or down-weighted influential observations — it identifies statistically significant spatial clusters of high or low values even when the attribute distribution contains extreme values that would distort the standard Gi*.	Robust 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.