"compositions": A unified R package to analyze compositional data

By K. Gerald van den Boogaart, Raimon Tolosana-Delgado. Computational Geosciences, 2008

552 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Environmental Engineering, Geophysics

View Paper: https://www.semanticscholar.org/paper/d5e8f49e6b6e44add1347167e672a19d871689be

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Pieter Vermeesch
2. John A. Silander
3. Alan E. Gelfand
4. G. Gloor
5. Eduardo Garzanti
6. Alberto Resentini
7. Thomas J. Leininger
8. Andrew D. Fernandes

In Environmental Engineering

1. Pieter Vermeesch
2. John A. Silander
3. Alan E. Gelfand
4. Eduardo Garzanti
5. Alberto Resentini
6. Thomas J. Leininger
7. Jenica M. Allen
8. Van Eijnatten

In Geophysics

1. John A. Silander
2. Alan E. Gelfand
3. Pieter Vermeesch
4. G. Gloor
5. Eduardo Garzanti
6. Alberto Resentini
7. Thomas J. Leininger
8. Andrew D. Fernandes

Citations in the corpus

• Unifying the analysis of high-throughput sequencing datasets: characterizing RNA-seq, 16S rRNA gene sequencing and selective growth experiments by compositional data analysis (2014, background): “Aitchison demonstrated that data mapping to the simplex must be transformed prior to analysis to prevent erroneous conclusions [12,17].”
• An R package for statistical provenance analysis (2016, methodology): “…to address this issue, which are scattered in many different places and implemented in a variety of different software environments (e.g van den Boogaart and Tolosana-Delgado, 2008; Ludwig, 2003; Marshall, 1996; Resentini et al., 2013; Sircombe, 2004; Sircombe and Hazelton, 2004; Templ et al.,…”
• On the use of archetypes as benchmarks (2008, unknown): “Hence, suitable methods developed for their analysis can be exploited to gain further insights into the data structure [39, 40].”
• Spatial Regression Modeling for Compositional Data With Many Zeros (2013, methodology): “Model fitting software for both transformations is available, e.g., using CoDaPack or the compositions package (van den Boogaart and Tolosana-Delgado, 2008) in R (R Core Team, 2012).”
• Ipsative measurement and the analysis of organizational values: an alternative approach for data analysis (2014, methodology): “The R-software package ‘compositions’ (Van den Boogaart 2005; Boogaart and Tolosana-Delgado 2008; Van den Boogaart et al. 2013) was used to compute the alternative current, and alternative preferred CFPs.”