An R Library for Compositional Data Analysis in Archaeometry

Compositional data naturally arises from the scientific analysis of the chemicalcomposition of archaeological material such as ceramic and glass artefacts. Data of thistype can be explored using a variety of techniques, from standard multivariate methodssuch as principal components analysis and cluster analysis, to methods based upon theuse of log-ratios. The general aim is to identify groups of chemically similar artefactsthat could potentially be used to answer questions of provenance.This paper will demonstrate work in progress on the development of a documentedlibrary of methods, implemented using the statistical package R, for the analysis ofcompositional data. R is an open source package that makes available very powerfulstatistical facilities at no cost. We aim to show how, with the aid of statistical softwaresuch as R, traditional exploratory multivariate analysis can easily be used alongside, orin combination with, specialist techniques of compositional data analysis.The library has been developed from a core of basic R functionality, together withpurpose-written routines arising from our own research (for example that reported atCoDaWork'03). In addition, we have included other appropriate publicly availabletechniques and libraries that have been implemented in R by other authors. Availablefunctions range from standard multivariate techniques through to various approaches tolog-ratio analysis and zero replacement. We also discuss and demonstrate a smallselection of relatively new techniques that have hitherto been little-used inarchaeometric applications involving compositional data. The application of the libraryto the analysis of data arising in archaeometry will be demonstrated; results fromdifferent analyses will be compared; and the utility of the various methods discussed

Compositional Data Analysis with R

R from http://www.r-project.org/ is ‘GNU S’ – a language and environment for statistical computingand graphics. The environment in which many classical and modern statistical techniques havebeen implemented, but many are supplied as packages. There are 8 standard packages and many moreare available through the cran family of Internet sites http://cran.r-project.org .We started to develop a library of functions in R to support the analysis of mixtures and our goal isa MixeR package for compositional data analysis that provides support foroperations on compositions: perturbation and power multiplication, subcomposition with or withoutresiduals, centering of the data, computing Aitchison’s, Euclidean, Bhattacharyya distances,compositional Kullback-Leibler divergence etc.graphical presentation of compositions in ternary diagrams and tetrahedrons with additional features:barycenter, geometric mean of the data set, the percentiles lines, marking and coloring ofsubsets of the data set, theirs geometric means, notation of individual data in the set . . .dealing with zeros and missing values in compositional data sets with R procedures for simpleand multiplicative replacement strategy,the time series analysis of compositional data.We’ll present the current status of MixeR development and illustrate its use on selected data sets

Real-life versus package insert: a post-marketing study on adverse-event rates of the virosomal hepatitis A vaccine Epaxal® in healthy travellers.

There are various methods to collect adverse events (AEs) in clinical trials. The methods how AEs are collected in vaccine trials is of special interest: solicited reporting can lead to over-reporting events that have little or no biological relationship to the vaccine. We assessed the rate of AEs listed in the package insert for the virosomal hepatitis A vaccine Epaxal(®), comparing data collected by solicited or unsolicited self-reporting. In an open, multi-centre post-marketing study, 2675 healthy travellers received single doses of vaccine administered intramuscularly. AEs were recorded based on solicited and unsolicited questioning during a four-day period after vaccination. A total of 2541 questionnaires could be evaluated (95.0% return rate). Solicited self-reporting resulted in significantly higher (p<0.0001) rates of subjects with AEs than unsolicited reporting, both at baseline (18.9% solicited versus 2.1% unsolicited systemic AEs) and following immunization (29.6% versus 19.3% local AEs; 33.8% versus 18.2% systemic AEs). This could indicate that actual reporting rates of AEs with Epaxal(®) may be substantially lower than described in the package insert. The distribution of AEs differed significantly between the applied methods of collecting AEs. The most common AEs listed in the package insert were reported almost exclusively with solicited questioning. The reporting of local AEs was more likely than that of systemic AEs to be influenced by subjects' sex, age and study centre. Women reported higher rates of AEs than men. The results highlight the need for detailing the methods how vaccine tolerability was reported and assessed.

An R Library for Compositional Data Analysis in Archaeometry

Compositional data naturally arises from the scientific analysis of the chemical composition of archaeological material such as ceramic and glass artefacts. Data of this type can be explored using a variety of techniques, from standard multivariate methods such as principal components analysis and cluster analysis, to methods based upon the use of log-ratios. The general aim is to identify groups of chemically similar artefacts that could potentially be used to answer questions of provenance. This paper will demonstrate work in progress on the development of a documented library of methods, implemented using the statistical package R, for the analysis of compositional data. R is an open source package that makes available very powerful statistical facilities at no cost. We aim to show how, with the aid of statistical software such as R, traditional exploratory multivariate analysis can easily be used alongside, or in combination with, specialist techniques of compositional data analysis. The library has been developed from a core of basic R functionality, together with purpose-written routines arising from our own research (for example that reported at CoDaWork'03). In addition, we have included other appropriate publicly available techniques and libraries that have been implemented in R by other authors. Available functions range from standard multivariate techniques through to various approaches to log-ratio analysis and zero replacement. We also discuss and demonstrate a small selection of relatively new techniques that have hitherto been little-used in archaeometric applications involving compositional data. The application of the library to the analysis of data arising in archaeometry will be demonstrated; results from different analyses will be compared; and the utility of the various methods discussed

Compositional Data Analysis with R

R from http://www.r-project.org/ is ‘GNU S’ – a language and environment for statistical computing and graphics. The environment in which many classical and modern statistical techniques have been implemented, but many are supplied as packages. There are 8 standard packages and many more are available through the cran family of Internet sites http://cran.r-project.org . We started to develop a library of functions in R to support the analysis of mixtures and our goal is a MixeR package for compositional data analysis that provides support for operations on compositions: perturbation and power multiplication, subcomposition with or without residuals, centering of the data, computing Aitchison’s, Euclidean, Bhattacharyya distances, compositional Kullback-Leibler divergence etc. graphical presentation of compositions in ternary diagrams and tetrahedrons with additional features: barycenter, geometric mean of the data set, the percentiles lines, marking and coloring of subsets of the data set, theirs geometric means, notation of individual data in the set . . . dealing with zeros and missing values in compositional data sets with R procedures for simple and multiplicative replacement strategy, the time series analysis of compositional data. We’ll present the current status of MixeR development and illustrate its use on selected data sets

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 are difficult to use correctly in standard statistical packages. In this paper we describe the new features of our freeware package, named CoDaPack, which implements most of the basic statistical methods suitable for compositional data. An example using real data is presented to illustrate the use of the package

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 a freeware package, named CoDaPack was created. This software implements most of the basic statistical methods suitable for compositional data. In this paper we describe the new version of the package that now is called CoDaPack3D. 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 knowledge of 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 be zoomed and, in 3D, rotated. Also a customization menu is included and outputs could be saved in jpeg format. Also this new version includes an interactive help and all dialog windows have been improved in order to facilitate its use. To use CoDaPack one has to access Excel© and introduce the data in a standard spreadsheet. These should be organized as a matrix where Excel© rows correspond to the observations and columns to the parts. The user executes macros that return numerical or graphical results. There are two kinds of numerical results: new variables and descriptive statistics, and both appear on the same sheet. Graphical output appears in independent windows. In the present version there are 8 menus, with a total of 38 submenus which, after some dialogue, directly call the corresponding macro. The dialogues ask the user to input variables and further parameters needed, as well as where to put these results. The web site http://ima.udg.es/CoDaPack contains this freeware package and only Microsoft Excel© under Microsoft Windows© is required to run the software. Kew words: Compositional data Analysis, Software

Adaptive integral assessment package for the A2UN@ project

This paper presents a first approach of Evaluation Engine Architecture (EEA) as proposal to support adaptive integral assessment, in the context of a virtual learning environment. The goal of our research is design an evaluation engine tool to assist in the whole assessment process within the A2UN@ project, linking that tool with the other key elements of a learning design (learning task, learning resources and learning support). The teachers would define the relation between knowledge, competencies, activities, resources and type of assessment. Providing this relation is possible obtain more accurate estimations of student's knowledge for adaptive evaluations and future recommendations. The process is supported by usage of educational standards and specifications and for an integral user modelling

Programa SPSS : Statistical Package for Social Sicences.

Se reseña la celebración del cursillo sobre 'Statistical Package for Social Sciences' en enero de 1980, en el Centro de Cálculo de la Universidad Politécnica de Barcelona, organizado por el Departamento de Investigación del INCIE, en el marco de las actividades del Seminario Permanente que sobre Metodología de la Investigación Educativa desarrolla este organismo. También, se ofrecen explicaciones teóricas y prácticas de este programa de tratamiento de la información llamado SPSS cuya aplicación se dirige, en especial, a la investigación en ciencias humanas.

Para un diagnóstico de la personalidad : un estudio sobre el cuestionario VTC-R.

1) Comprobar si el contenido de las características de personalidad según Reimplein, como se recogen en el VTC-R, coinciden con las variables del Cuestionario de Personalidad 16 PF de Cattell.2) Descubrir, a través del análisis factorial, distintos tipos de personalidad, y compulsar, de alguna manera, las semejanzas y diferencias entre ambos sexos. 22 sujetos masculinos y 202 femeninos, alumnos de una escuela de Formación del Profesorado de E.G.B. Para el objetivo de este trabajo es necesario precisar el contenido de las variables del cuestionario VTC-R, y para comprobar de alguna forma las diferencias existentes entre ambos sexos, se utiliza los resultados del análisis factorial. Se considera, en primer lugar el análisis factorial de las variables VTC-R, en sí mismo, describiéndose cada uno de los tipos resultantes. La presencia de variables del 16 PF en un análisis ulterior permite precisar el sentido y significado de las variables VTC-R, que prácticamente permanecen igualmente estructuradas. Tipos de personalidad responden a los diversos factores; y sobre la base de coincidencias de cada factor, se fija lo común a ambos sexos y se destaca lo específico de cada uno. Se llega asía una estructura compleja de la Personalidad. El análisis factorial se ha calculado por el correspondiente programa Factor Statistical Package of Social Sciences (SPSS). El análisis de la muestra ha sido realizado a través del Cuestionario VTC-R, y del Cuestionario de Personalidad de Cattell: 16 PF. Ambos cuestionarios se refieren a elementos constitutivos de la personalidad. El cuestionario VTC-R se encuentra en fase de experimentación. Se miden tres dimensiones de la personalidad: vitalidad, temperamento y carácter, con 46 variables. Aquí analiza los resultados de una primera aplicación en contraste con el 16 Pf de Cattell. El cuestionario 16 PF, corresponde a la edición de 1985 según publicaciones T.E.A. 1) Aparece una confirmación suficiente de la correspondencia entre las preguntas del cuestionario y las descripciones de las variables en Reimplein. queda manifiesto la relación entre la parte teórica y la empírica. 2) Aunque no son abundantes, si son suficientes para sugerir y confirmar diferencias entre los sexos, que suelen considerarse en la investigación científica.3) El hombre aparece como más egoísta, con mayor afán de poder, y entra con facilidad en la competencia por su gran deseo de verse valorado, con una tendencia más acentuada del yo.4) En la mujer, se destaca la tendencia a las actividades sociales, en que se suelen comportar de una forma refinada. Suelen predominar los sentimientos en su actuar, su capacidad receptiva es grande y va acompañada de gran sensibilidad y delicadeza.5) El 16 PF nos presenta al hombre como un ser racional; esta racionalidad le hace sentirse y ser liberal, con deseo de comprobar en vez de afirmar las cosas sin más.6) Las mujeres, con mayor dependencia de los sentimientos en su actuar, aparecen de poca tolerancia ante las frustraciones, son más conformistas, y, a al vez, más escrupulosas, con mayor sentido de exigencia y perseverancia, esto según el 16 PF.

A three-dimensional magnetometer for motion sensing of a balloon-carried atmospheric measurement package

An instrument is described which carries three orthogonal geomagnetic field sensors on a standard meteorological balloon package, to sense rapid motion and position changes during ascent through the atmosphere. Because of the finite data bandwidth available over the UHF radio link, a burst sampling strategy is adopted. Bursts of 9s of measurements at 3.6Hz are interleaved with periods of slow data telemetry lasting 25s. Calculation of the variability in each channel is used to determine position changes, a method robust to periods of poor radio signals. During three balloon ascents, variability was found repeatedly at similar altitudes, simultaneously in each of three orthogonal sensors carried. This variability is attributed to atmospheric motions. It is found that the vertical sensor is least prone to stray motions, and that the use of two horizontal sensors provides no additional information over a single horizontal sensor

Decision making for HVAC&R system selection for a typical office building in the UK

Demands for thermal comfort, better indoor air quality together with lower environmental impacts have had ascending trends in the last decade. In many circumstances, these demands could not be fully covered through the soft approach of bioclimatic design like optimisation of the building orientation and internal layout. This is mostly because of the dense urban environment and building internal energy loads. In such cases, heating, ventilation, air-conditioning and refrigeration (HVAC&R) systems make a key role to fulfill the requirements of indoor environment. Therefore, it is required to select the most proper HVAC&R system. In this study, a robust decision making approach for HVAC&R system selection is proposed. Technical performance, economic aspect and environmental impacts of 36 permutations of primary and secondary systems are taken into account to choose the most proper HVAC&R system for a case study office building. The building is a representative for the dominant form of office buildings in the UK. Dynamic performance evaluation of HVAC&R alternatives using TRNSYS package together with life cycle energy cost analysis provides a reliable basis for decision making. Six scenarios broadly cover the decision makers' attitudes on HVAC&R system selection which are analysed through Analytical Hierarchy Process (AHP). One of the significant outcomes reveals that, despite both the higher energy demand and more investment requirements associated with compound heating, cooling and power system (CCHP); this system is one of the top ranked alternatives due to the lower energy cost and C02 emissions. The sensitivity analysis reveals that in all six scenarios, the first five top ranked alternatives are not changed. Finally, the proposed approach and the results could be used by researchers and designers especially in the early stages of a design process in which all involved bodies face the lack of time, information and tools for evaluation of a variety of systems.

Unwriting food labels: discursive challenges in the regulation of package claims

This article examines the challenges resulting from the regulation of written discourse on food packages. It uses as a case study Hong Kong’s strict new food-labeling law that requires distributers and retailers to remove certain nutritional claims from packages of imported food before they sell them. This practice of redacting unlawful text on packages requires that distributers and retailers engage in complex processes of discursive reasoning, and it some- times results in packages that are difficult for customers to interpret. The case study highlights important issues in the regulation of commercial texts concerning collaboration, intertextuality, and the conflicts that can arise when the principals, authors, and animators of such texts have different agendas.