השוואת שיטות
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| פונקציית K של ריפלי× | ניתוח נקודות חמות Getis-Ord Gi*× | |
|---|---|---|
| תחום | ניתוח מרחבי | ניתוח מרחבי |
| משפחה≠ | Hypothesis test | Regression model |
| שנת המקור≠ | 1977 | 1992 |
| הוגה השיטה≠ | Brian Ripley | Arthur Getis and J. Keith Ord |
| סוג≠ | Spatial point pattern test | Local spatial statistic |
| מקור מכונן≠ | 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 ↗ |
| כינויים≠ | 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 |
| קשורות≠ | 2 | 4 |
| תקציר≠ | 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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