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| 시공간 공간 자기상관분석× | 공간 패널 데이터 모형 (고정효과/확률효과)× | |
|---|---|---|
| 분야 | 공간분석 | 공간분석 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1981–1992 | 2014 |
| 창시자≠ | Cliff & Ord; extended by Anselin and others | Elhorst; Lee & Yu |
| 유형≠ | Spatial autocorrelation statistic | Spatial econometric panel model |
| 원전≠ | 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 ↗ |
| 별칭 | 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) |
| 관련≠ | 5 | 4 |
| 요약≠ | 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). |
| ScholarGate데이터셋 ↗ |
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