Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Odhad hustoty jádra pro panelová data× | Analýza panelových hotspotů× | |
|---|---|---|
| Obor | Prostorová analýza | Prostorová analýza |
| Rodina | Regression model | Regression model |
| Rok vzniku≠ | 1962 (KDE); panel extension: 1990s–2000s | 1992 (Gi* statistic); 2004 (longitudinal/panel extension) |
| Tvůrce≠ | Parzen (1962); Silverman (1986); extended to panel contexts in spatial econometrics literature | Weisburd et al. (longitudinal application); Getis & Ord (foundational Gi* statistic) |
| Typ≠ | Nonparametric density estimation | Spatio-temporal hot spot detection |
| Původní zdroj≠ | Parzen, E. (1962). On estimation of a probability density function and mode. Annals of Mathematical Statistics, 33(3), 1065-1076. DOI ↗ | 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. DOI ↗ |
| Další názvy | 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 |
| Příbuzné≠ | 5 | 4 |
| Shrnutí≠ | 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. |
| ScholarGateDatová sada ↗ |
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