Salīdzināt metodes

	Robustā Getisa-Ord Gi* statistika	Lokālais Morana I (LISA)
Nozare	Telpiskā analīze	Telpiskā analīze
Saime	Regression model	Regression model
Izcelsmes gads	1992 (base); robust variants circa 2000s–2010s	1995
Autors	Getis & Ord (base statistic); robust extensions developed in subsequent spatial statistics literature	Luc Anselin
Tips	Local spatial statistic	Local spatial autocorrelation statistic
Pirmavots	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.
Citi nosaukumi	Robust Gi*, Robust local Gi star, outlier-resistant hot spot analysis, robust local spatial autocorrelation Gi*	Local Indicator of Spatial Association, LISA statistic, Anselin Local Moran, local spatial autocorrelation index
Saistītās	5	6
Kopsavilkums	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*.	Local Moran's I, introduced by Luc Anselin in 1995, is a Local Indicator of Spatial Association (LISA) that decomposes global spatial autocorrelation into location-specific contributions. For every observation it produces a signed statistic and a significance value, enabling researchers to identify spatial clusters (high-high, low-low) and spatial outliers (high-low, low-high) on a map.