Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Универсално кригиране (Кригиране с тренд)× | Географски претеглена регресия (GWR)× | |
|---|---|---|
| Област | Пространствен анализ | Пространствен анализ |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 1969 | 2002 |
| Създател≠ | Georges Matheron | Fotheringham, Brunsdon & Charlton |
| Тип≠ | Geostatistical interpolation with spatial trend | Local spatial regression |
| Основополагащ източник≠ | Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246–1266. DOI ↗ | Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168 |
| Други названия | kriging with a trend, kriging with drift, trend kriging, evrensel kriging | GWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR) |
| Свързани≠ | 3 | 5 |
| Резюме≠ | 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. | Geographically Weighted Regression is a local regression method, introduced by Fotheringham, Brunsdon and Charlton (2002), that allows the regression coefficients to vary across space. Instead of one global equation, it fits a separate set of coefficients at every location, capturing spatial heterogeneity in the relationships. |
| ScholarGateНабор от данни ↗ |
|
|