विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| वैश्विक सामान्य क्रिगिंग× | ऑर्डिनरी क्रिगिंग× | |
|---|---|---|
| क्षेत्र | स्थानिक विश्लेषण | स्थानिक विश्लेषण |
| परिवार | Regression model | Regression model |
| उद्भव वर्ष≠ | 1951–1963 | 1963 |
| प्रवर्तक≠ | Danie G. Krige; formalized by Georges Matheron | Georges Matheron (formalising D.G. Krige's empirical work) |
| प्रकार | Geostatistical interpolation | Geostatistical interpolation |
| मौलिक स्रोत≠ | Cressie, N. A. C. (1993). Statistics for Spatial Data (revised ed.). Wiley. ISBN: 978-0471002550 | Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246-1266. DOI ↗ |
| उपनाम | ordinary kriging, OK, global kriging, stationary ordinary kriging | OK, kriging interpolation, geostatistical interpolation, BLUE spatial predictor |
| संबंधित≠ | 5 | 4 |
| सारांश≠ | Global Ordinary Kriging (GOK) is the canonical geostatistical interpolation method that estimates values at unsampled locations as a weighted linear combination of nearby observations. It fits a single variogram model to the entire dataset, enforcing a global stationarity assumption, and produces optimal unbiased predictions along with quantified prediction uncertainty at every interpolated point. | Ordinary Kriging (OK) is the standard geostatistical method for interpolating a continuous spatial variable at unsampled locations. It derives optimal, unbiased weights from the spatial covariance structure of the data, making it the Best Linear Unbiased Predictor (BLUP) under stationarity assumptions. Unlike simpler distance-based methods, it also provides a prediction uncertainty (kriging variance) at every interpolated point. |
| ScholarGateडेटासेट ↗ |
|
|