विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| रिप्ले K फलन× | गेटीस-ऑर्ड Gi* हॉट स्पॉट विश्लेषण× | |
|---|---|---|
| क्षेत्र | स्थानिक विश्लेषण | स्थानिक विश्लेषण |
| परिवार≠ | Hypothesis test | Regression model |
| उद्भव वर्ष≠ | 1977 | 1992 |
| प्रवर्तक≠ | Brian Ripley | Arthur Getis and J. Keith Ord |
| प्रकार≠ | Spatial point pattern test | Local spatial statistic |
| मौलिक स्रोत≠ | Ripley, B. D. (1977). Modelling spatial patterns. Journal of the Royal Statistical Society: Series B, 39(2), 172–212. DOI ↗ | Getis, A. & Ord, J.K. (1992). The Analysis of Spatial Association by Use of Distance Statistics. Geographical Analysis, 24(3), 189–206. DOI ↗ |
| उपनाम≠ | Ripley's K Function, Second-Order Intensity Function, K(d) Function, Ripley K Fonksiyonu | hot spot analysis, cold spot analysis, Gi* statistic, local Gi statistic |
| संबंधित≠ | 2 | 4 |
| सारांश≠ | The Ripley K function, introduced by Brian Ripley in 1977, is a second-order summary statistic for spatial point patterns. It measures how the number of points within a given distance d of a typical point compares to what would be expected under complete spatial randomness (CSR). Widely used in ecology, epidemiology, criminology, and geography, the K function reveals whether events cluster, disperse, or distribute randomly across a study area at multiple spatial scales simultaneously. | 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). |
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