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Porovnat metody

Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.

Odhad hustoty jádra pro panelová data×Prostorová regrese panelových dat×
OborProstorová analýzaProstorová analýza
RodinaRegression modelRegression model
Rok vzniku1962 (KDE); panel extension: 1990s–2000s1988-2014
TvůrceParzen (1962); Silverman (1986); extended to panel contexts in spatial econometrics literatureAnselin, Elhorst, and colleagues in spatial econometrics
TypNonparametric density estimationSpatial panel regression
Původní zdrojParzen, E. (1962). On estimation of a probability density function and mode. Annals of Mathematical Statistics, 33(3), 1065-1076. DOI ↗Elhorst, J. P. (2014). Spatial Econometrics: From Cross-Sectional Data to Spatial Panels. Springer. ISBN: 978-3642403408
Další názvyPanel KDE, longitudinal kernel density estimation, repeated-measures KDE, panel nonparametric density estimationspatial panel model, panel spatial econometrics, spatial panel data regression, PSR
Příbuzné56
ShrnutíPanel 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.
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ScholarGatePorovnat metody: Panel Kernel Density Estimation · Panel Spatial Regression. Získáno 2026-06-15 z https://scholargate.app/cs/compare