Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Ukridingi wa Ulimwengu (Ukridingi wenye Mwenendo)× | Cokriging× | |
|---|---|---|
| Nyanja | Uchanganuzi wa Kimaeneo | Uchanganuzi wa Kimaeneo |
| Familia | Regression model | Regression model |
| Mwaka wa asili≠ | 1969 | 1963 |
| Mwanzilishi≠ | Georges Matheron | Georges Matheron (geostatistics); multivariate extension |
| Aina≠ | Geostatistical interpolation with spatial trend | Multivariate geostatistical interpolation |
| Chanzo asilia | Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246–1266. DOI ↗ | Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246–1266. DOI ↗ |
| Majina mbadala≠ | kriging with a trend, kriging with drift, trend kriging, evrensel kriging | co-kriging, multivariate kriging, ortak kriging |
| Zinazohusiana | 3 | 3 |
| Muhtasari≠ | 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. | Cokriging extends kriging to use one or more correlated secondary variables to improve prediction of a primary variable. When the variable of interest is sparsely sampled but a related, cheaper-to-measure variable is densely sampled, cokriging borrows strength from the secondary variable through their cross-correlation, yielding more accurate interpolations and prediction variances than kriging the primary variable alone. |
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