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| 시공간 공간 자기상관분석× | 공간 시차 모형 (SAR / 공간 자기회귀)× | |
|---|---|---|
| 분야 | 공간분석 | 공간분석 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1981–1992 | 1988 |
| 창시자≠ | Cliff & Ord; extended by Anselin and others | Anselin (textbook formalisation); LeSage & Pace |
| 유형≠ | Spatial autocorrelation statistic | Spatial autoregressive regression |
| 원전≠ | Clifford, P., Richardson, S., & Hemon, D. (1989). Assessing the significance of the correlation between two spatial processes. Biometrics, 45(1), 123–134. DOI ↗ | Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic. DOI ↗ |
| 별칭 | STSA, spatiotemporal autocorrelation, space-time Moran's I, temporal spatial dependence | SAR model, spatial autoregressive model, spatial lag, Uzamsal Gecikme Modeli (SAR / Spatial Lag) |
| 관련 | 5 | 5 |
| 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 Lag Model is an autoregressive regression that assumes spatial dependence in the dependent variable itself: the outcome values of neighbouring units enter the model as an explanatory term (ρWy). It was formalised in Anselin's Spatial Econometrics (1988) and developed further by LeSage and Pace (2009), and it decomposes spillover effects into direct, indirect, and total impacts. |
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