Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Interpolación Espacial por Kriging× | Análisis de Puntos Calientes Getis-Ord Gi*× | |
|---|---|---|
| Campo | Análisis espacial | Análisis espacial |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1963 | 1992 |
| Autor original≠ | Georges Matheron (formalised geostatistics) | Arthur Getis and J. Keith Ord |
| Tipo≠ | Geostatistical spatial interpolation | Local spatial statistic |
| Fuente seminal≠ | Matheron, G. (1963). Principles of Geostatistics. Economic Geology, 58(8), 1246–1266. DOI ↗ | Getis, A. & Ord, J.K. (1992). The Analysis of Spatial Association by Use of Distance Statistics. Geographical Analysis, 24(3), 189–206. DOI ↗ |
| Alias≠ | geostatistical interpolation, Gaussian process regression (geostatistics), ordinary kriging, Kriging (Mekânsal Enterpolasyon) | hot spot analysis, cold spot analysis, Gi* statistic, local Gi statistic |
| Relacionados≠ | 5 | 4 |
| Resumen≠ | 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. | Getis-Ord Gi* is a local spatial statistic, introduced by Getis and Ord in 1992 and refined in 1995, that compares the value at each location and its neighbours against the global mean to identify statistically significant clusters of high values (hot spots) and low values (cold spots). |
| ScholarGateConjunto de datos ↗ |
|
|