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| Stima della Densità del Kernel su Dati Panel× | Regressione Spaziale su Dati Panel× | |
|---|---|---|
| Campo | Analisi spaziale | Analisi spaziale |
| Famiglia | Regression model | Regression model |
| Anno di origine≠ | 1962 (KDE); panel extension: 1990s–2000s | 1988-2014 |
| Ideatore≠ | Parzen (1962); Silverman (1986); extended to panel contexts in spatial econometrics literature | Anselin, Elhorst, and colleagues in spatial econometrics |
| Tipo≠ | Nonparametric density estimation | Spatial panel regression |
| Fonte seminale≠ | Parzen, 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 |
| Alias | Panel KDE, longitudinal kernel density estimation, repeated-measures KDE, panel nonparametric density estimation | spatial panel model, panel spatial econometrics, spatial panel data regression, PSR |
| Correlati≠ | 5 | 6 |
| Sintesi≠ | 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. |
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