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| 面板核密度估计× | 面板热点分析× | |
|---|---|---|
| 领域 | 空间分析 | 空间分析 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1962 (KDE); panel extension: 1990s–2000s | 1992 (Gi* statistic); 2004 (longitudinal/panel extension) |
| 提出者≠ | Parzen (1962); Silverman (1986); extended to panel contexts in spatial econometrics literature | Weisburd et al. (longitudinal application); Getis & Ord (foundational Gi* statistic) |
| 类型≠ | Nonparametric density estimation | Spatio-temporal hot spot detection |
| 开创性文献≠ | 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 ↗ |
| 别名 | 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 |
| 相关≠ | 5 | 4 |
| 摘要≠ | 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. |
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