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| 패널 네트워크 기반 공간 분석× | 네트워크 기반 공간 분석× | |
|---|---|---|
| 분야 | 공간분석 | 공간분석 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 2000s–2010s | 1990s–2000s |
| 창시자≠ | Developed from LeSage & Pace spatial econometrics and Elhorst panel spatial frameworks | Atsuyuki Okabe and colleagues |
| 유형≠ | Panel spatial regression | Spatial network model |
| 원전≠ | LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247 | Okabe, A., Satoh, T., Furuta, T., Sugihara, K., & Okano, K. (2006). Generalized network Voronoi diagrams: Concepts, computational methods, and applications. International Journal of Geographical Information Science, 22(9), 965–994. DOI ↗ |
| 별칭 | panel spatial network analysis, longitudinal network spatial analysis, panel network spatial econometrics, PNBSA | network spatial analysis, network-constrained spatial analysis, spatial network analysis, NBSA |
| 관련≠ | 5 | 3 |
| 요약≠ | Panel Network-Based Spatial Analysis extends standard spatial econometric models to repeated-measures (panel) data by representing spatial dependence through network connectivity rather than simple geographic proximity. It captures how units connected in a network influence each other's outcomes over time, while controlling for unit-level and time-level fixed effects. | Network-based spatial analysis (NBSA) analyzes the distribution and interaction of spatial phenomena constrained to a network structure — such as roads, railways, or rivers — using network distance rather than straight-line (Euclidean) distance. It is the appropriate framework whenever movement, proximity, or risk is governed by the underlying network topology rather than open space. |
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