CoDaPack 2.0: a stand-alone, multi-platform compositional software

Historically CoDaPack 3D has intended to be a software of Compositional Data with an easy and intuitive way of use. For this reason from the beginning it has been associated to Excel, a software known and used for many people. However, over the years different versions of Excel and Windows have been appeared and CoDaPack has had to be adapted to these new versions due to some incompatibilities. For this reason, and also because of CoDaPack only works with Excel under windows, the Girona Compositional Data Group has decided to implement a new software with at least the same capabilities and the same profile of users but independent of any other software. The graphical user interface has three different areas: The variables area, the data area and the results area which has a textual output window and independent graphical output. Also, because the new CoDaPack is being developed under Java code, the final software is going to work in any platform having a Java Virtual Machine: Windows, Linux and other Unix based systems

Compositional random data: a routine for CoDaPack

Generation of random variables are needed in the simulations of many natural process. For some random variables, di erent methodologies are known, specially into euclidean spaces. In this paper a routine for dealing with random variables into a simplex space with the Aitchison geometry is presented. The routine has been implemented for the CoDaPack, a freeware software developed to be used for users with minimum programming skills

Proceedings of the 6th International Workshop on Compositional Data Analysis: Girona, 1-7 de juny de 2015

Llibre d'actes del 6è International Workshop on Compositional Data Analysis, celebrat a Girona els dies 1 a 7 de juny de 201

CoDaPack 2.0: a stand-alone, Multi-platform Compositional Software

Historically CoDaPack 3D has intended to be a software of Compositional Data with an easy and intuitive way of use. For this reason from the beginning it has been associated to Excel, a software known and used for many people. However, over the years different versions of Excel and Windows have been appeared and CoDaPack has had to be adapted to these new versions due to some incompatibilities. For this reason, and also because of CoDaPack only works with Excel under windows, the Girona Compositional Data Group has decided to implement a new software with at least the same capabilities and the same profile of users but independent of any other software. The graphical user interface has three different areas: The variables area, the data area and the results area which has a textual output window and independent graphical output. Also, because the new CoDaPack is being developed under Java code, the final software is going to work in any platform having a Java Virtual Machine: Windows, Linux and other Unix based system

Anàlisi de matrius quadrades no simètriques: un enfocament integral usant anàlisi de correspondències

En este artículo se presenta una propuesta integrada de análisis de matrices cuadradas no simétricas mediante análisis de correspondencias. En ella se han integrado las dos principales familias de metodologías que proponen soluciones a la problemática inherente a estos tipos de tablas: las diagonales sobrecargadas y los ceros estructurales. Se aplica al ejemplo de estudio de los movimientos de población debidos al trabajo entre las 41 comarcas catalanas

Anàlisi de matrius quadrades no simètriques: un enfocament integral usant anàlisi de correspondències

En este artículo se presenta una propuesta integrada de análisis de matrices cuadradas no simétricas mediante análisis de correspondencias. En ella se han integrado las dos principales familias de metodologías que proponen soluciones a la problemática inherente a estos tipos de tablas: las diagonales sobrecargadas y los ceros estructurales. Se aplica al ejemplo de estudio de los movimientos de población debidos al trabajo entre las 41 comarcas catalanas

New Features of CoDaPack. An Userfriendly Compositional Data Package

The statistical analysis of compositional data is commonly used in geological studies.As is well-known, compositions should be treated using logratios of parts, which aredifficult to use correctly in standard statistical packages. In this paper we describe thenew features of our freeware package, named CoDaPack, which implements most of thebasic statistical methods suitable for compositional data. An example using real data ispresented to illustrate the use of the packageGeologische Vereinigung; Institut d’Estadística de Catalunya; International Association for Mathematical Geology; Patronat de l’Escola Politècnica Superior de la Universitat de Girona; Fundació privada: Girona, Universitat i Futur; Càtedra Lluís Santaló d’Aplicacions de la Matemàtica; Consell Social de la Universitat de Girona; Ministerio de Ciencia i Tecnología

CODAPACK3D. A new version of Compositional Data Package

The statistical analysis of compositional data should be treated using logratios of parts,which are difficult to use correctly in standard statistical packages. For this reason afreeware package, named CoDaPack was created. This software implements most of thebasic statistical methods suitable for compositional data.In this paper we describe the new version of the package that now is calledCoDaPack3D. It is developed in Visual Basic for applications (associated with Excel©),Visual Basic and Open GL, and it is oriented towards users with a minimum knowledgeof computers with the aim at being simple and easy to use.This new version includes new graphical output in 2D and 3D. These outputs could bezoomed and, in 3D, rotated. Also a customization menu is included and outputs couldbe saved in jpeg format. Also this new version includes an interactive help and alldialog windows have been improved in order to facilitate its use.To use CoDaPack one has to access Excel© and introduce the data in a standardspreadsheet. These should be organized as a matrix where Excel© rows correspond tothe observations and columns to the parts. The user executes macros that returnnumerical or graphical results. There are two kinds of numerical results: new variablesand descriptive statistics, and both appear on the same sheet. Graphical output appearsin independent windows. In the present version there are 8 menus, with a total of 38submenus which, after some dialogue, directly call the corresponding macro. Thedialogues ask the user to input variables and further parameters needed, as well aswhere to put these results. The web site http://ima.udg.es/CoDaPack contains thisfreeware package and only Microsoft Excel© under Microsoft Windows© is required torun the software.Kew words: Compositional data Analysis, SoftwareGeologische Vereinigung; Institut d’Estadística de Catalunya; International Association for Mathematical Geology; Càtedra Lluís Santaló d’Aplicacions de la Matemàtica; Generalitat de Catalunya, Departament d’Innovació, Universitats i Recerca; Ministerio de Educación y Ciencia; Ingenio 2010

Compositional Random Data: a Routine for CoDaPack

Generation of random variables are needed in the simulations of many natural process. For some random variables, different methodologies are known, specially into euclidean spaces. In this paper a routine for dealing with random variables into a simplex space with the Aitchison geometry is presented. The routine has been implemented for the CoDaPack, a freeware software developed to be used for users with minimum programming skill

Two More Things about Compositional Biplots: Quality of Projection and Inclusion of Supplementary Elements

The biplot is a widely and powerful methodology used with multidimensional data sets to describe and display the relationships between observations and variables in an easy way. Compositional data consist of positive vectors each of which is constrained to have a constant sum; due to this property standard biplots can not be performed with compositional data, instead of a previous transformation of the data is performed. Due to this constant sum constraint, a transformation of data is needed before performing a biplot and, consequently, special interpretation rules are required. However, these rules can only be safely applied when the elements of a biplot have a good quality of projection, for which a new measure is introduced in this paper. Also, we extend the compositional biplot defined by Aitchison and Greenacre on 2002, in order to include the display supplementary elements that are not used in the definition of the compositional biplot. Different types of supplementary elements are considered: supplementary parts of the composition, supplementary continuous variables external to the composition, supplementary categorical variables and supplementary observations. The projection of supplementary parts of the composition is done by means of the equivalence of clr and lr biplots. The other supplementary projections are done by classical methodology. Both the qualities of projections and the supplementary projections are explained using real geological data: a sample of 72 observations of soil in an area about 20 km west of Kiev in the area south of Kiev Polessi