手法を比較
選択した手法を並べて確認できます。異なる行はハイライト表示されます。
| ベイズ正規クリギング× | 空間的自己相関× | |
|---|---|---|
| 分野 | 空間分析 | 空間分析 |
| 系統 | Regression model | Regression model |
| 提唱年≠ | 1993 | 1950 |
| 提唱者≠ | Handcock & Stein (1993); Diggle & Ribeiro (2007) | P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995) |
| 種類≠ | Bayesian geostatistical interpolation | Spatial statistic / exploratory spatial data analysis |
| 原典≠ | Diggle, P. J., & Ribeiro, P. J. (2007). Model-Based Geostatistics. Springer. ISBN: 978-0387329079 | Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗ |
| 別名 | Bayesian kriging, BOK, geostatistical Bayesian interpolation, Bayesian spatial prediction | spatial dependence, geographic autocorrelation, spatial clustering measure, SA |
| 関連 | 5 | 5 |
| 概要≠ | Bayesian Ordinary Kriging is a geostatistical interpolation method that combines classical ordinary kriging with a Bayesian framework to jointly estimate the spatial covariance parameters and produce predictions at unsampled locations. Unlike plug-in kriging, it propagates uncertainty about variogram parameters through to the predictive distribution, yielding more honest uncertainty quantification. | Spatial autocorrelation quantifies the degree to which a variable's values at nearby locations resemble each other more (positive autocorrelation) or less (negative autocorrelation) than expected by chance. Global indices such as Moran's I summarise the pattern across the entire study area, while local variants reveal clusters and outliers at the level of individual observations. |
| ScholarGateデータセット ↗ |
|
|