השוואת שיטות
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| ניתוח נקודות חמות במרחב-זמן× | ניתוח נקודות חמות (Local Getis-Ord Gi*)× | |
|---|---|---|
| תחום | ניתוח מרחבי | ניתוח מרחבי |
| משפחה | Regression model | Regression model |
| שנת המקור≠ | 1997–2015 | 1992–1995 |
| הוגה השיטה≠ | Kulldorff (spatial scan statistic); operationalized for time-series bins by Esri (Emerging Hot Spot Analysis) | Arthur Getis and J. Keith Ord |
| סוג≠ | Spatiotemporal cluster detection | Local spatial association statistic |
| מקור מכונן≠ | Kulldorff, M. (1997). A spatial scan statistic. Communications in Statistics: Theory and Methods, 26(6), 1481–1496. 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 | emerging hot spot analysis, space-time cube hot spot, spatiotemporal hot spot detection, STHA | Gi* statistic, Getis-Ord Gi*, local G-star, hot spot statistic |
| קשורות | 5 | 5 |
| תקציר≠ | Space-Time Hot Spot Analysis extends the classic Getis-Ord Gi* statistic across repeated time slices organised in a space-time cube. By testing each location-time bin for statistically significant clustering of high or low values, then examining the sequence of results over time, it identifies whether clusters are new, intensifying, persistent, sporadic, or diminishing — giving analysts a dynamic picture of how hot and cold spots evolve. | The Local Getis-Ord Gi* statistic identifies statistically significant spatial clusters of high values (hot spots) and low values (cold spots) within a study area. Unlike global measures, it produces a z-score for every location, revealing where concentrated clustering occurs and with what statistical confidence. |
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