Salīdzināt metodes

	Telpiskās Autokorelācijas Paplašinājums Laikā un Telpā	Telpiskās nobīdes modelis (SAR / Telpiskais autoregresīvais)
Nozare	Telpiskā analīze	Telpiskā analīze
Saime	Regression model	Regression model
Izcelsmes gads	1981–1992	1988
Autors	Cliff & Ord; extended by Anselin and others	Anselin (textbook formalisation); LeSage & Pace
Tips	Spatial autocorrelation statistic	Spatial autoregressive regression
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. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic.
Citi nosaukumi	STSA, spatiotemporal autocorrelation, space-time Moran's I, temporal spatial dependence	SAR model, spatial autoregressive model, spatial lag, Uzamsal Gecikme Modeli (SAR / Spatial Lag)
Saistītās	5	5
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.	The Spatial Lag Model is an autoregressive regression that assumes spatial dependence in the dependent variable itself: the outcome values of neighbouring units enter the model as an explanatory term (ρWy). It was formalised in Anselin's Spatial Econometrics (1988) and developed further by LeSage and Pace (2009), and it decomposes spillover effects into direct, indirect, and total impacts.