Salīdzināt metodes

	Telpiskās Autokorelācijas Paplašinājums Laikā un Telpā	Lokālais Morana I (LISA)
Nozare	Telpiskā analīze	Telpiskā analīze
Saime	Regression model	Regression model
Izcelsmes gads	1981–1992	1995
Autors	Cliff & Ord; extended by Anselin and others	Luc Anselin
Tips	Spatial autocorrelation statistic	Local spatial autocorrelation statistic
Pirmavots	Clifford, P., Richardson, S., & Hemon, D. (1989). Assessing the significance of the correlation between two spatial processes. Biometrics, 45(1), 123–134.	Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115.
Citi nosaukumi	STSA, spatiotemporal autocorrelation, space-time Moran's I, temporal spatial dependence	Local Indicator of Spatial Association, LISA statistic, Anselin Local Moran, local spatial autocorrelation index
Saistītās	5	6
Kopsavilkums	Space-Time Spatial Autocorrelation extends classic spatial autocorrelation measures — most notably Moran's I — to data that vary across both geographic units and time periods. It detects whether nearby locations that are also temporally close tend to share similar attribute values, revealing clusters, trends, or anomalies that purely spatial or purely temporal analyses would miss.	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.