Сравнение методов

	Оценка плотности ядра в панельных данных (Panel Kernel Density Estimation)	Панельная пространственная регрессия
Область	Пространственный анализ	Пространственный анализ
Семейство	Regression model	Regression model
Год появления	1962 (KDE); panel extension: 1990s–2000s	1988-2014
Автор метода	Parzen (1962); Silverman (1986); extended to panel contexts in spatial econometrics literature	Anselin, Elhorst, and colleagues in spatial econometrics
Тип	Nonparametric density estimation	Spatial panel regression
Основополагающий источник	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
Другие названия	Panel KDE, longitudinal kernel density estimation, repeated-measures KDE, panel nonparametric density estimation	spatial panel model, panel spatial econometrics, spatial panel data regression, PSR
Связанные	5	6
Сводка	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.