Comparer des méthodes

	Estimation de Densité par Noyau sur Données de Panel	Analyse de points chauds en panel
Domaine	Analyse spatiale	Analyse spatiale
Famille	Regression model	Regression model
Année d'origine	1962 (KDE); panel extension: 1990s–2000s	1992 (Gi* statistic); 2004 (longitudinal/panel extension)
Auteur d'origine	Parzen (1962); Silverman (1986); extended to panel contexts in spatial econometrics literature	Weisburd et al. (longitudinal application); Getis & Ord (foundational Gi* statistic)
Type	Nonparametric density estimation	Spatio-temporal hot spot detection
Source fondatrice	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.
Alias	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
Apparentées	5	4
Résumé	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.