方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 克里金空间插值× | 空间面板数据模型（固定效应/随机效应）× | |
|---|---|---|
| 领域 | 空间分析 | 空间分析 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1963 | 2014 |
| 提出者≠ | Georges Matheron (formalised geostatistics) | Elhorst; Lee & Yu |
| 类型≠ | Geostatistical spatial interpolation | Spatial econometric panel model |
| 开创性文献≠ | Matheron, G. (1963). Principles of Geostatistics. Economic Geology, 58(8), 1246–1266. DOI ↗ | Elhorst, J. P. (2014). Spatial Econometrics: From Cross-Sectional Data to Spatial Panels. Springer. DOI ↗ |
| 别名 | geostatistical interpolation, Gaussian process regression (geostatistics), ordinary kriging, Kriging (Mekânsal Enterpolasyon) | spatial panel FE/RE, spatial econometric panel, spatial lag/error panel, Uzamsal Panel Modeli (Spatial Panel FE/RE) |
| 相关≠ | 5 | 4 |
| 摘要≠ | Kriging is a geostatistical method that predicts the value of a continuous variable at unmeasured locations from nearby measurements, using the spatial correlation structure captured by a variogram. Formalised by Georges Matheron in 1963, it is the best linear unbiased predictor (BLUP) for spatial data and comes in Ordinary, Universal, and Co-Kriging forms. | 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). |
| ScholarGate数据集 ↗ |
|
|