Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Uhalali wa Nafasi-Wakati wa Kina× | Muundo wa Data wa Paneli wa Angani (FE/RE)× | |
|---|---|---|
| Nyanja | Uchanganuzi wa Kimaeneo | Uchanganuzi wa Kimaeneo |
| Familia | Regression model | Regression model |
| Mwaka wa asili≠ | 1981–1992 | 2014 |
| Mwanzilishi≠ | Cliff & Ord; extended by Anselin and others | Elhorst; Lee & Yu |
| Aina≠ | Spatial autocorrelation statistic | Spatial econometric panel model |
| Chanzo asilia≠ | Clifford, P., Richardson, S., & Hemon, D. (1989). Assessing the significance of the correlation between two spatial processes. Biometrics, 45(1), 123–134. DOI ↗ | Elhorst, J. P. (2014). Spatial Econometrics: From Cross-Sectional Data to Spatial Panels. Springer. DOI ↗ |
| Majina mbadala | STSA, spatiotemporal autocorrelation, space-time Moran's I, temporal spatial dependence | spatial panel FE/RE, spatial econometric panel, spatial lag/error panel, Uzamsal Panel Modeli (Spatial Panel FE/RE) |
| Zinazohusiana≠ | 5 | 4 |
| Muhtasari≠ | Space-Time Spatial Autocorrelation extends classic spatial autocorrelation measures — most notably Moran's I — to data that vary across both geographic units and time periods. It detects whether nearby locations that are also temporally close tend to share similar attribute values, revealing clusters, trends, or anomalies that purely spatial or purely temporal analyses would miss. | The spatial panel model is a family of econometric models that adds spatial dependence to panel data (units observed over time). It combines fixed- or random-effects panel structure with spatial lag, spatial error, or spatial Durbin components, and is developed in the modern spatial-econometrics literature by Elhorst (2014) and Lee & Yu (2010). |
| ScholarGateSeti ya data ↗ |
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