Salīdzināt metodes

	Analīze karstajiem punktiem panelī	Telpiskās un laikiskās karstās vietas analīze
Nozare	Telpiskā analīze	Telpiskā analīze
Saime	Regression model	Regression model
Izcelsmes gads	1992 (Gi* statistic); 2004 (longitudinal/panel extension)	1997–2015
Autors	Weisburd et al. (longitudinal application); Getis & Ord (foundational Gi* statistic)	Kulldorff (spatial scan statistic); operationalized for time-series bins by Esri (Emerging Hot Spot Analysis)
Tips	Spatio-temporal hot spot detection	Spatiotemporal cluster detection
Pirmavots	Weisburd, D., Bushway, S., Lum, C., & Yang, S.-M. (2004). Trajectories of crime at places: A longitudinal study of street segments in the city of Seattle. Criminology, 42(2), 283-321.	Kulldorff, M. (1997). A spatial scan statistic. Communications in Statistics: Theory and Methods, 26(6), 1481–1496.
Citi nosaukumi	longitudinal hot spot analysis, repeated cross-sectional hot spot analysis, spatio-temporal hot spot detection, panel Getis-Ord analysis	emerging hot spot analysis, space-time cube hot spot, spatiotemporal hot spot detection, STHA
Saistītās	4	5
Kopsavilkums	Panel Hot Spot Analysis applies hot spot detection — typically via the Getis-Ord Gi* statistic — repeatedly across multiple time periods on the same spatial units, enabling researchers to track where clusters of high or low values persist, emerge, or dissolve over time. It bridges cross-sectional spatial statistics with longitudinal panel methods.	Space-Time Hot Spot Analysis extends the classic Getis-Ord Gi* statistic across repeated time slices organised in a space-time cube. By testing each location-time bin for statistically significant clustering of high or low values, then examining the sequence of results over time, it identifies whether clusters are new, intensifying, persistent, sporadic, or diminishing — giving analysts a dynamic picture of how hot and cold spots evolve.