Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Bray-Curtisova dissimilarity× | Hellingerova vzdálenost× | |
|---|---|---|
| Obor | Rozhodování | Rozhodování |
| Rodina | MCDM | MCDM |
| Rok vzniku≠ | 1957 | 1909 |
| Tvůrce≠ | John Bray and John T. Curtis | Ernst Hellinger |
| Typ≠ | Ecological community similarity measure | Symmetric metric for probability distributions |
| Původní zdroj≠ | Bray, J. R., & Curtis, J. T. (1957). An ordination of the upland forest communities of southern Wisconsin. Ecological Monographs, 27(4), 325-349. DOI ↗ | Hellinger, E. (1909). Neue Begründung der Theorie quadratischer Formen von unendlichvielen Veränderlichen. Journal für die Reine und Angewandte Mathematik, 136, 210-271. DOI ↗ |
| Další názvy≠ | Bray-Curtis index, Sorensen-Bray-Curtis, percentage difference | Bhattacharyya distance, Hellinger metric |
| Příbuzné≠ | 3 | 2 |
| Shrnutí≠ | Bray-Curtis dissimilarity is a quantitative measure of compositional difference between two samples, widely used in ecology and community analysis. Introduced by John Bray and John T. Curtis in 1957 for comparing forest communities, this index ranges from 0 (identical composition) to 1 (completely different). It is sensitive to abundance differences and is particularly effective for abundance data such as species counts, microbial populations, or preference intensities. | Hellinger distance is a symmetric, bounded metric that measures the difference between two probability distributions. Rooted in the work of Ernst Hellinger (1909) and later formalized in statistical divergence by Anil Bhattacharyya (1946), this distance ranges from 0 (identical distributions) to 1. It is a true metric satisfying all mathematical distance properties and is particularly well-suited for comparing probability distributions in a symmetric, numerically stable manner. |
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