Salīdzināt metodes

	Panel Kernel Density Estimation	Analīze karstajiem punktiem panelī
Nozare	Telpiskā analīze	Telpiskā analīze
Saime	Regression model	Regression model
Izcelsmes gads	1962 (KDE); panel extension: 1990s–2000s	1992 (Gi* statistic); 2004 (longitudinal/panel extension)
Autors	Parzen (1962); Silverman (1986); extended to panel contexts in spatial econometrics literature	Weisburd et al. (longitudinal application); Getis & Ord (foundational Gi* statistic)
Tips	Nonparametric density estimation	Spatio-temporal hot spot detection
Pirmavots	Parzen, E. (1962). On estimation of a probability density function and mode. Annals of Mathematical Statistics, 33(3), 1065-1076.	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.
Citi nosaukumi	Panel KDE, longitudinal kernel density estimation, repeated-measures KDE, panel nonparametric density estimation	longitudinal hot spot analysis, repeated cross-sectional hot spot analysis, spatio-temporal hot spot detection, panel Getis-Ord analysis
Saistītās	5	4
Kopsavilkums	Panel Kernel Density Estimation (Panel KDE) extends the standard kernel density estimator to panel (longitudinal) data, estimating smooth density surfaces for spatial or attribute variables observed across multiple units and time periods. It reveals how the distribution of a phenomenon shifts, concentrates, or disperses over time and across groups, making it a natural tool for tracking spatial patterns in repeated-measures or panel datasets.	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.