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Advances in principal balances for compositional data

Autor
Martín-Fernández, J. A.; Pawlowsky, V.; Egozcue, J. J.; Tolosana-Delgado, R.
Tipus d'activitat
Article en revista
Revista
Mathematical geosciences
Data de publicació
2018-04
Volum
50
Número
3
Pàgina inicial
273
Pàgina final
298
DOI
https://doi.org/10.1007/s11004-017-9712-z Obrir en finestra nova
Repositori
https://www.researchgate.net/publication/321235488_Advances_in_Principal_Balances_for_Compositional_Data Obrir en finestra nova
URL
https://link.springer.com/article/10.1007%2Fs11004-017-9712-z Obrir en finestra nova
Resum
Compositional data analysis requires selecting an orthonormal basis with which to work on coordinates. In most cases this selection is based on a data driven criterion. Principal component analysis provides bases that are, in general, functions of all the original parts, each with a different weight hindering their interpretation. For interpretative purposes, it would be better to have each basis component as a ratio or balance of the geometric means of two groups of parts, leaving irrelevant pa...
Paraules clau
Aitchison norm, Cluster analysis, Compositions, Isometric logratio coordinates, Principal component analysis, Simplex
Grup de recerca
COSDA-UPC - COmpositional and Spatial Data Analysis
LIM/UPC - Laboratori d'Enginyeria Marítima

Participants

  • Martín Fernández, Josep Antoni  (autor)
  • Pawlowsky Glahn, Vera  (autor)
  • Egozcue Rubi, Juan José  (autor)
  • Tolosana Delgado, Raimon  (autor)