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| Crime Concentration Index× | Getis-Ord Gi* karstā analīze× | |
|---|---|---|
| Nozare≠ | Criminology | Telpiskā analīze |
| Saime≠ | Process / pipeline | Regression model |
| Izcelsmes gads≠ | 1989 | 1992 |
| Autors≠ | Lawrence Sherman, Patrick Gartin & Michael Buerger; David Weisburd | Arthur Getis and J. Keith Ord |
| Tips≠ | Descriptive concentration measure for crime across micro-places | Local spatial statistic |
| Pirmavots≠ | Sherman, L. W., Gartin, P. R., & Buerger, M. E. (1989). Hot spots of predatory crime: Routine activities and the criminology of place. Criminology, 27(1), 27–56. DOI ↗ | Getis, A. & Ord, J.K. (1992). The Analysis of Spatial Association by Use of Distance Statistics. Geographical Analysis, 24(3), 189–206. DOI ↗ |
| Citi nosaukumi≠ | Crime Concentration at Place, Hot-Spot Concentration Measure, Cumulative Crime Concentration, Law of Crime Concentration | hot spot analysis, cold spot analysis, Gi* statistic, local Gi statistic |
| Saistītās | 4 | 4 |
| Kopsavilkums≠ | The crime concentration index quantifies how unevenly crime is distributed across micro-geographic places such as street segments or addresses. Building on Sherman, Gartin, and Buerger's 1989 discovery that a small fraction of addresses produces most calls for police service, and formalized in Weisburd's 2015 'law of crime concentration', it expresses the share of all crime accounted for by the most crime-prone places. | 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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