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。
| ベイジアン・クリーギング(モデルベース地球統計学)× | ユニバーサル・クリーギング(トレンド付きクリーギング)× | |
|---|---|---|
| 分野 | 空間分析 | 空間分析 |
| 系統 | Regression model | Regression model |
| 提唱年≠ | 1993–1998 | 1969 |
| 提唱者≠ | Diggle, Tawn & Moyeed; Handcock & Stein | Georges Matheron |
| 種類≠ | Bayesian spatial interpolation | Geostatistical interpolation with spatial trend |
| 原典≠ | Diggle, P. J., Tawn, J. A., & Moyeed, R. A. (1998). Model-based geostatistics. Journal of the Royal Statistical Society: Series C (Applied Statistics), 47(3), 299–350. DOI ↗ | Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246–1266. DOI ↗ |
| 別名 | Bayesian geostatistics, model-based geostatistics, Bayesian spatial interpolation, stochastic kriging | kriging with a trend, kriging with drift, trend kriging, evrensel kriging |
| 関連≠ | 5 | 3 |
| 概要≠ | Bayesian Kriging embeds classical geostatistical interpolation inside a full probabilistic framework. Instead of treating variogram parameters as fixed point estimates, it places prior distributions on them and updates these priors with observed spatial data to obtain a posterior distribution. Predictions at unsampled locations are then marginalised over this uncertainty, yielding honest predictive intervals that account for both spatial dependence and parameter uncertainty. | Universal kriging generalizes ordinary kriging to data whose mean varies systematically across space — a spatial trend or 'drift'. It models the mean as a function of the coordinates (or covariates) and krigs the residuals, so it can interpolate variables that drift in a preferred direction, such as temperature falling with latitude or a pollutant gradient, while still returning prediction variances. |
| ScholarGateデータセット ↗ |
|
|