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Universitat de Girona. Departament dâ€™InformÃ tica i MatemÃ tica Aplicada  
Parent, SergeÃ‰tienne
Covington, Kyle R. 

2011 May 12  
The compositional analyst must use a series of software to transform raw compositional data and run statistical analyses on them. Tools for compositional data analysis are available in R, an open source widelyused statistical computing environment. However, using R requires prior programming knowledge. RedR is an opensource, userfriendly visual data flow interface based on R. The interface uses principles of pipeline programming where functions are represented as icons, termed widgets, and data flows from one function to another by drawing lines between them on a canvas. RedR is able to perform common data analysis tasks (hypothesis tests, analysis of variance, regressions, principal component analysis, data cloud plots, bar plots, biplots, etc.). We have developed a novel RedR package which implements the compositions package in R. Our compositions package can be used to perform compositional data operations over raw data (closure, additive, centered and isometric log ratio transformations, perturbations and powering, etc.), and create compositional plots (ternary diagrams, ilrdendrograms, etc.) without prior programming knowledge, after few basic operations. The objective of this work is to present RedR and its compositions package using an application example for geochemical data. The network of widgets provides an easytofollow stepbystep procedure to run a large number of operations available in R, hence facilitating the tasks of the compositional data analyst. Furthermore, the entire analysis network can be saved and reloaded. Reports can be generated from the widget network to document and share results. Nonprogrammers can have an easy access to the advanced tools available in compositions analysis  
application/pdf  
http://hdl.handle.net/10256/13646  
eng  
Universitat de Girona. Departament dâ€™InformÃ tica i MatemÃ tica Aplicada  
CoDaWork 2011. The 4th International Workshop on Compositional Data Analysis  
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EstadÃstica matemÃ tica  Congressos
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Compositional Data Analysis with RedR  
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