Un Parc a la mida de Girona: el Parc Científic i Tecnològic de la UdG

El Parc Científic i Tecnològic de la Universitat de Girona es disposa a acollir gairebé mig miler d'investigadors, una cinquantena d'empreses i grups de recerca amb la voluntat de consolidar-se com a trampolí tecnològic per a diversos sectors industrials gironins. En el Parc que s'està bastint a la Creueta conflueixen els esforços de la Universitat, l'Administració i l'empresa per fer de Girona un lloc capdavanter en la indústria del coneixement

L'Experiència dels pobles indígenes, amb milers d'anys d'història, està entrant a la universitat"

Andrés Fábregas Puig és el rector de la Universitat Intercultural de Chiapas, a Mèxic. El mes de març passat va visitar la UdG i va pronunciar una conferència a la Càtedra Unesco de la Universitat sobre l'actualitat sociopolítica del seu país

Quinze anys d'Universitat

Breu repàs històric dels 15 anys de la Universitat amb les paraules dels rectors

La MAT encén el debat de l'energia a Girona

Opinions sobre el projecte de línia de molt alta tensió a les comarques gironines i anàlisi de l'impacte ambiental

Història urbana de Girona: una història dibuixada

El Dr. Josep Maria Nolla ha contribuït de manera decisiva al coneixement dels orígens de la ciutat de Girona. El seu treball i el dels seus companys en aquesta aventura de recerca és a l'abast de tothom en la col·lecció "Història urbana de Girona", que ha tingut, la tardor del 2007, una traducció brillant en l'exposició "De Kerunta a Gerunda. Els orígens de la ciutat"

Biotech Girona: l'espai de la biotecnologia

Espais a mida, tota mena de facilitats i bona companyia. Sembla l'anunci d'una promoció immobiliària, però això és el que ofereix el Biogech Girona, un lloc dins el Parc Científic i Tecnològic que proposa espais a mida per establir-se en un entorn d'excel·lència en la recerca. El Parc acaba d'obrir la convocatòria per seleccionar les empreses interessades

Batxillerat: camins cap a la Universitat

El batxillerat és un intens camí que recorre l'estudiant i que en bona part dels casos té com a meta la universitat. En el trajecte hi ha uns quants esculls, com el treball de recerca i la selectivitat. Els joves han de prémer fort l'accelerador si volen assolir la fita consignada. El suport de la família i els professors els pot fer el viatge una mica més fàcil

Medicina a Girona

La Universitat de Girona impartirà la titulació de Medicina en una facultat pròpia a partir del curs 2008-2009. Es proposa un pla d'estudis innovador que la convertirà en un centre pioner a Catalunya, elaborat en complicitat amb els diversos agents clínics i assistencials de la demarcació, per garantir la màxima qualitat de la docència i la recerca

Física bàsica per a la universitat [versió html]

Llibre preparat per ser utilitzat com a material de text de Física bàsica, assignatura de lliure elecció de 6 crèdits, del segon quadrimestre dels nous plans d'estudis d' Informàtica Tècnica (especialitats de Sistemes i de Gestió) i d' Enginyeria Tècnica Agrícola (especialitats d' Explotacions Agropecuàries i d' Indústries Agràries i Agroalimentàries) de la Universitat de Girona. L’objectiu estratègic és donar als alumnes, en un sol quadrimestre, la formació necessària per a seguir un curs de primer de física, així com que l’alumne tingui agilitat en la transformació d’unitats, s’habituï a comprovar la raonabilitat dels resultats i sigui capaç de superar la noció que la física és un conjunt de formules inconnexes

Compositional data analysis: where we are and where should we be heading?

We take stock of the present position of compositional data analysis, of what has been achieved in the last 20 years, and then make suggestions as to what may be sensible avenues of future research. We take an uncompromisingly applied mathematical view, that the challenge of solving practical problems should motivate our theoretical research; and that any new theory should be thoroughly investigated to see if it may provide answers to previously abandoned practical considerations. Indeed a main theme of this lecture will be to demonstrate this applied mathematical approach by a number of challenging examples

Some last thoughts on compositional data analysis

One of the disadvantages of old age is that there is more past than future: this, however, may be turned into an advantage if the wealth of experience and, hopefully, wisdom gained in the past can be reflected upon and throw some light on possible future trends. To an extent, then, this talk is necessarily personal, certainly nostalgic, but also self critical and inquisitive about our understanding of the discipline of statistics. A number of almost philosophical themes will run through the talk: search for appropriate modelling in relation to the real problem envisaged, emphasis on sensible balances between simplicity and complexity, the relative roles of theory and practice, the nature of communication of inferential ideas to the statistical layman, the inter-related roles of teaching, consultation and research. A list of keywords might be: identification of sample space and its mathematical structure, choices between transform and stay, the role of parametric modelling, the role of a sample space metric, the underused hypothesis lattice, the nature of compositional change, particularly in relation to the modelling of processes. While the main theme will be relevance to compositional data analysis we shall point to substantial implications for general multivariate analysis arising from experience of the development of compositional data analysis…

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

A Factor analysis of hidrochemical composition of Llobregat river basin

Hydrogeological research usually includes some statistical studies devised to elucidate mean background state, characterise relationships among different hydrochemical parameters, and show the influence of human activities. These goals are achieved either by means of a statistical approach or by mixing models between end-members. Compositional data analysis has proved to be effective with the first approach, but there is no commonly accepted solution to the end-member problem in a compositional framework. We present here a possible solution based on factor analysis of compositions illustrated with a case study. We find two factors on the compositional bi-plot fitting two non-centered orthogonal axes to the most representative variables. Each one of these axes defines a subcomposition, grouping those variables that lay nearest to it. With each subcomposition a log-contrast is computed and rewritten as an equilibrium equation. These two factors can be interpreted as the isometric log-ratio coordinates (ilr) of three hidden components, that can be plotted in a ternary diagram. These hidden components might be interpreted as end-members. We have analysed 14 molarities in 31 sampling stations all along the Llobregat River and its tributaries, with a monthly measure during two years. We have obtained a bi-plot with a 57% of explained total variance, from which we have extracted two factors: factor G, reflecting geological background enhanced by potash mining; and factor A, essentially controlled by urban and/or farming wastewater. Graphical representation of these two factors allows us to identify three extreme samples, corresponding to pristine waters, potash mining influence and urban sewage influence. To confirm this, we have available analysis of diffused and widespread point sources identified in the area: springs, potash mining lixiviates, sewage, and fertilisers. Each one of these sources shows a clear link with one of the extreme samples, except fertilisers due to the heterogeneity of their composition. This approach is a useful tool to distinguish end-members, and characterise them, an issue generally difficult to solve. It is worth note that the end-member composition cannot be fully estimated but only characterised through log-ratio relationships among components. Moreover, the influence of each endmember in a given sample must be evaluated in relative terms of the other samples. These limitations are intrinsic to the relative nature of compositional data

The agreement between ipsative and normative questionnaires using compositional data analysis techniques

The main instrument used in psychological measurement is the self-report questionnaire. One of its major drawbacks however is its susceptibility to response biases. A known strategy to control these biases has been the use of so-called ipsative items. Ipsative items are items that require the respondent to make between-scale comparisons within each item. The selected option determines to which scale the weight of the answer is attributed. Consequently in questionnaires only consisting of ipsative items every respondent is allotted an equal amount, i.e. the total score, that each can distribute differently over the scales. Therefore this type of response format yields data that can be considered compositional from its inception. Methodological oriented psychologists have heavily criticized this type of item format, since the resulting data is also marked by the associated unfavourable statistical properties. Nevertheless, clinicians have kept using these questionnaires to their satisfaction. This investigation therefore aims to evaluate both positions and addresses the similarities and differences between the two data collection methods. The ultimate objective is to formulate a guideline when to use which type of item format. The comparison is based on data obtained with both an ipsative and normative version of three psychological questionnaires, which were administered to 502 first-year students in psychology according to a balanced within-subjects design. Previous research only compared the direct ipsative scale scores with the derived ipsative scale scores. The use of compositional data analysis techniques also enables one to compare derived normative score ratios with direct normative score ratios. The addition of the second comparison not only offers the advantage of a better-balanced research strategy. In principle it also allows for parametric testing in the evaluation

Multivariate ARIMA Compositional Time Series Analysis

A compositional time series is obtained when a compositional data vector is observed at different points in time. Inherently, then, a compositional time series is a multivariate time series with important constraints on the variables observed at any instance in time. Although this type of data frequently occurs in situations of real practical interest, a trawl through the statistical literature reveals that research in the field is very much in its infancy and that many theoretical and empirical issues still remain to be addressed. Any appropriate statistical methodology for the analysis of compositional time series must take into account the constraints which are not allowed for by the usual statistical techniques available for analysing multivariate time series. One general approach to analyzing compositional time series consists in the application of an initial transform to break the positive and unit sum constraints, followed by the analysis of the transformed time series using multivariate ARIMA models. In this paper we discuss the use of the additive log-ratio, centred log-ratio and isometric log-ratio transforms. We also present results from an empirical study designed to explore how the selection of the initial transform affects subsequent multivariate ARIMA modelling as well as the quality of the forecasts