Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Estimación de Densidad Kernel para Datos de Panel× | Autocorrelación Espacial en Datos de Panel× | |
|---|---|---|
| Campo | Análisis espacial | Análisis espacial |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1962 (KDE); panel extension: 1990s–2000s | 1988–2003 |
| Autor original≠ | Parzen (1962); Silverman (1986); extended to panel contexts in spatial econometrics literature | Anselin, L.; Elhorst, J. P. |
| Tipo≠ | Nonparametric density estimation | Diagnostic test / exploratory statistic |
| Fuente seminal≠ | Parzen, E. (1962). On estimation of a probability density function and mode. Annals of Mathematical Statistics, 33(3), 1065-1076. DOI ↗ | Anselin, L. (2013). Spatial Econometrics: Methods and Models. Springer Netherlands. (Originally published 1988.) ISBN: 978-9401577991 |
| Alias | Panel KDE, longitudinal kernel density estimation, repeated-measures KDE, panel nonparametric density estimation | spatial autocorrelation in panel data, panel spatial dependence, spatio-temporal autocorrelation, cross-sectional dependence in panels |
| Relacionados | 5 | 5 |
| Resumen≠ | 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 Autocorrelation measures whether observations that are geographically close also tend to have similar values across repeated time periods. It extends classic cross-sectional spatial autocorrelation statistics such as Moran's I to panel data, enabling researchers to detect spatial dependence consistently over time and to diagnose whether a panel regression model requires a spatial component. |
| ScholarGateConjunto de datos ↗ |
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