Cited by 704Geochemistry and Geologic MappingAdvanced Statistical Methods and ModelsStatistical Methods and Applications

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Compositional Data Analysis: Theory and Applications

V. Pawlowsky Glahn, Antonella Buccianti·2011·Wiley eBooks

DOI 10.1002/9781119976462

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Abstract

It is difficult to imagine that the statistical analysis of compositional data has been a major issue of concern for more than 100 years. It is even more difficult to realize that so many statisticians and users of statistics are unaware of the particular problems affecting compositional data, as well as their solutions. The issue of spurious correlation'', as the situation was phrased by Karl Pearson back in 1897, affects all data that measures parts of some whole, such as percentages, proportions, ppm and ppb. Such measurements are present in all fields of science, ranging from geology, biology, environmental sciences, forensic sciences, medicine and hydrology. This book presents the history and development of compositional data analysis along with Aitchison's log-ratio approach. Compositional Data Analysis describes the state of the art both in theoretical fields as well as applications in the different fields of science.

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Background
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Background
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BackgroundMethod
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“In statistics, we refer to compositional data (Aitchison 1986; Pawlowsky-Glahn and Buccianti 2011; PawlowskyGlahn et al. 2015) as to observations for which the ratios are informative.”
Method
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Self-citation
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“While various distributions exist for modeling compositional data (such as those discussed in [1] and more recently in [7]), zeros in the data corresponding to an absence of a component (that is, essential zeros rather than rounded zeros) are typically problematic since traditional approaches for dealing with composit…”
Background
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Robust biomarker identification in a two-class problem based on pairwise log-ratios
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General approach to coordinate representation of compositional tables
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“As regards vector compositions, balances represent the most popular class of orthonormal coordinates that was recently successfully applied in a number of real-world studies (Pawlowsky-Glahn & Buccianti, 2011).”
Background
Dynamic Predictive Density Combinations for Large Data Sets in Economics and FinancePreprint
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The Moss Biomonitoring Method and Neutron Activation Analysis in Assessing Pollution by Trace Elements in Selected Polish National Parks
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“Because concentration represents the amount of a selected substance in the total amount of all components, its analysis requires application of appropriate mathematical methods (Aitchison 2003; Pawlowsky-Glahn and Buccianti 2011).”
BackgroundMethod

Authors: Glahn, V. P., & Buccianti, A.
ORCID: Antonella Buccianti
Venue: Wiley eBooks
Publisher: Wiley
Published: 2011-07-28
DOI: 10.1002/9781119976462
OpenAlex: W571770348
Cited by: 704
References: 0
Citations by year: 2026: 30 · 2025: 38 · 2024: 34 · 2023: 40 · 2022: 45 · 2021: 71 · 2020: 71 · 2019: 46 · 2018: 61 · 2017: 60 · 2016: 52 · 2015: 42 · 2014: 47 · 2013: 37 · 2012: 22
FWCI: 14.85
Type: book
Language: en
Open access: closed
Licence: doi.wiley.com/10.1002/tdm_license_1.1 (tdm)
Locations: Wiley eBooks (publishedVersion)
Florence Research (University of Florence) (submittedVersion)
Topics: Physical Sciences › Earth and Planetary Sciences › Geochemistry and Petrology › Geochemistry and Geologic Mapping
Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
Keywords: compositional data analysis, spurious correlations, parts and wholes

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