Notes
As a comment, Greenacre (2011) published a paper “Measuring subcompositional incoherence” to show that the ideal of subcompositional coherence could be approximated by some methods that are not logratio-based. The proposed quantitative measurement of incoherence (i.e. lack of coherence) was quite straightforward and many numerical examples were included. Yet in the present paper the authors, at the end of Sect. 2.1, misrepresent this approach by saying, in their defence of strict coherence: “Incoherence is, in general, difficult to measure, or even check, numerically (Greenacre 2011)”.
References
Aitchison J (1986) The statistical analysis of compositional data. Chapman & Hall, London. Reprinted in 2003 with additional material by Blackburn Press. https://doi.org/10.1002/bimj.4710300705
Aitchison J (1997) The one-hour course in compositional data analysis, or compositional data analysis is easy. In: Pawlowsky Glahn V (ed) Proceedings of the 3rd annual conference of the International Association for Mathematical Geology, pp 3–35. CIMNE, Barcelona. https://www.iamg.org/images/File/documents/bios/Krumbein_recipients_pdfs/1997-Aitchison-One-hour-course-reduced.pdf. Last accessed 16 Apr 2019
Aitchison J (2003) Compositional data analysis: where are we and where should we be heading? Keynote address. CODAWORK 2003. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.580.9544. Last accessed 16 Apr 2019
Aitchison J (2008) The single principle of compositional data analysis, continuing fallacies, confusions and misunderstandings and some suggested remedies. Keynote address, CODAWORK 2008. https://core.ac.uk/download/pdf/132548276.pdf. Last accessed 16 Apr 2019
Atkinson AB (1970) On the measurement of inequality. J Econ Theory 2:244–263
Buccianti A (2015) The FOREGS repository: modelling variability in stream water on a continental scale revising classical diagrams from CoDA (compositional data analysis) perspective. J Geochem Explor 154:94–104
Greenacre M (2010) Biplots in practice. BBVA Foundation, Bilbao. www.multivariatestatistics.org. Last accessed 30 June 2019
Greenacre M (2011) Measuring subcompositional incoherence. Math Geosc 43:681–693
Greenacre M (2018a) Variable selection in compositional data analysis, using pairwise logratios. Math Geosci. https://doi.org/10.1007/s11004-018-9754-x
Greenacre M (2018b) Compositional data analysis in practice. Chapman & Hall, Boca Raton
Greenacre M, Grunsky E, Bacon-Shone J (2019) A comparison of amalgamation and isometric logratios in compositional data analysis. Comput Geosci (submitted). https://www.researchgate.net/publication/332656109_A_comparison_of_amalgamation_and_isometric_logratios_in_compositional_data_analysis. Last accessed 30 June 2019
Mallows C (2006) Tukey’s paper after 40 years (with discussion). Technometrics 48:319–336
Morton J, Sanders J, Quinn RA et al (2017) Balance trees reveal microbial niche differentiation. mSystems 2(1):e00162-16. https://doi.org/10.1128/mSystems.00162-16
Tukey JW (1962) The future of data analysis. Ann Math Stat 33:1–67
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
This comment refers to the invited paper available at: https://doi.org/10.1007/s11749-019-00670-6.
Rights and permissions
About this article
Cite this article
Greenacre, M. Comments on: Compositional data: the sample space and its structure. TEST 28, 644–652 (2019). https://doi.org/10.1007/s11749-019-00673-3
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11749-019-00673-3