Comparer des méthodes

	Estimation de Densité par Noyau sur Données de Panel	Régression Spatiale sur Données de Panel
Domaine	Analyse spatiale	Analyse spatiale
Famille	Regression model	Regression model
Année d'origine	1962 (KDE); panel extension: 1990s–2000s	1988-2014
Auteur d'origine	Parzen (1962); Silverman (1986); extended to panel contexts in spatial econometrics literature	Anselin, Elhorst, and colleagues in spatial econometrics
Type	Nonparametric density estimation	Spatial panel regression
Source fondatrice	Parzen, E. (1962). On estimation of a probability density function and mode. Annals of Mathematical Statistics, 33(3), 1065-1076.	Elhorst, J. P. (2014). Spatial Econometrics: From Cross-Sectional Data to Spatial Panels. Springer. ISBN: 978-3642403408
Alias	Panel KDE, longitudinal kernel density estimation, repeated-measures KDE, panel nonparametric density estimation	spatial panel model, panel spatial econometrics, spatial panel data regression, PSR
Apparentées	5	6
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 Spatial Regression extends standard panel data models by explicitly accounting for spatial dependence among cross-sectional units observed over time. It combines the temporal control of panel fixed or random effects with a spatial weights matrix that encodes geographic or network proximity, yielding unbiased and efficient estimates when observations are spatially correlated across units.