השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| 'C' של Geary למרחב-זמן× | מדדי התאגדות מרחבית מקומית של זמן-מרחב (ST-LISA)× | |
|---|---|---|
| תחום | ניתוח מרחבי | ניתוח מרחבי |
| משפחה | Regression model | Regression model |
| שנת המקור≠ | 1954 / 2010s | 1995 (LISA); space-time extensions developed 2000s–2010s |
| הוגה השיטה≠ | Geary (1954); extended to space-time by Anselin and others | Extension of Anselin (1995) LISA framework to the space-time domain |
| סוג≠ | Spatial autocorrelation statistic | Local spatial statistic (space-time) |
| מקור מכונן≠ | Geary, R. C. (1954). The Contiguity Ratio and Statistical Mapping. The Incorporated Statistician, 5(3), 115-145. DOI ↗ | Anselin, L. (1995). Local indicators of spatial association — LISA. Geographical Analysis, 27(2), 93–115. DOI ↗ |
| כינויים | ST-Geary's C, spatiotemporal Geary C, space-time contiguity ratio, space-time local spatial autocorrelation | ST-LISA, space-time LISA, spatiotemporal local indicators of spatial association, STLISA |
| קשורות | 6 | 6 |
| תקציר≠ | Space-Time Geary's C extends the classical Geary contiguity ratio to panel or longitudinal spatial data, measuring autocorrelation across both geographic neighbors and adjacent time periods simultaneously. Values below 1 indicate positive space-time clustering; values above 1 indicate dispersion, and a value near 1 suggests random arrangement across the space-time lattice. | Space-Time Local Indicators of Spatial Association (ST-LISA) extend the classic LISA framework of Anselin (1995) into the temporal dimension, identifying locations that exhibit statistically significant spatial clustering or spatial outlier behavior consistently or intermittently across multiple time periods. They decompose global space-time autocorrelation into local contributions, revealing where and when spatial clusters emerge, persist, or dissolve. |
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