Log-contrast and Orthonormal Log-ratio Coordinates for Compositional Data with a Total
Josep Antoni Martín-Fernández () and
Carles Barceló-Vidal ()
Additional contact information
Josep Antoni Martín-Fernández: University of Girona, Department of IMAE
Carles Barceló-Vidal: University of Girona, Department of IMAE
A chapter in Advances in Contemporary Statistics and Econometrics, 2021, pp 509-524 from Springer
Abstract:
Abstract Compositional data require an appropriate statistical analysis because they provide the relative importance of the parts of a whole. Methods based on log-ratio coordinates give a consistent framework for analyzing this type of data. Any statistical model including variables created using the original parts should be formulated according to the geometry of the simplex. This geometry includes the log-contrast: a simple way to express a set of log-ratios in a linear form. Basic concepts and properties of log-ratios, log-contrasts, and orthonormal coordinates are revisited. In addition, we introduce an approach that includes both the log-ratio orthonormal coordinates and an auxiliary variable carrying absolute information. We illustrate the approach through the principal component analysis and discriminant analysis of real data sets.
Date: 2021
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-73249-3_26
Ordering information: This item can be ordered from
http://www.springer.com/9783030732493
DOI: 10.1007/978-3-030-73249-3_26
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().