92 resultados para Vidal Alcover, Jaume
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First application of compositional data analysis techniques to Australian election data
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Precision of released figures is not only an important quality feature of official statistics, it is also essential for a good understanding of the data. In this paper we show a case study of how precision could be conveyed if the multivariate nature of data has to be taken into account. In the official release of the Swiss earnings structure survey, the total salary is broken down into several wage components. We follow Aitchison's approach for the analysis of compositional data, which is based on logratios of components. We first present diferent multivariate analyses of the compositional data whereby the wage components are broken down by economic activity classes. Then we propose a number of ways to assess precision
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This paper presents a procedure that allows us to determine the preference structures (PS) associated to each of the different groups of actors that can be identified in a group decision making problem with a large number of individuals. To that end, it makes use of the Analytic Hierarchy Process (AHP) (Saaty, 1980) as the technique to solve discrete multicriteria decision making problems. This technique permits the resolution of multicriteria, multienvironment and multiactor problems in which subjective aspects and uncertainty have been incorporated into the model, constructing ratio scales corresponding to the priorities relative to the elements being compared, normalised in a distributive manner (wi = 1). On the basis of the individuals’ priorities we identify different clusters for the decision makers and, for each of these, the associated preference structure using, to that end, tools analogous to those of Multidimensional Scaling. The resulting PS will be employed to extract knowledge for the subsequent negotiation processes and, should it be necessary, to determine the relative importance of the alternatives being compared using anyone of the existing procedures
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It is well known that regression analyses involving compositional data need special attention because the data are not of full rank. For a regression analysis where both the dependent and independent variable are components we propose a transformation of the components emphasizing their role as dependent and independent variables. A simple linear regression can be performed on the transformed components. The regression line can be depicted in a ternary diagram facilitating the interpretation of the analysis in terms of components. An exemple with time-budgets illustrates the method and the graphical features
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Two contrasting case studies of sediment and detrital mineral composition are investigated in order to outline interactions between chemical composition and grain size. Modern glacial sediments exhibit a strong dependence of the two parameters due to the preferential enrichment of mafic minerals, especially biotite, in the fine-grained fractions. On the other hand, the composition of detrital heavy minerals (here: rutile) appears to be not systematically related to grain-size, but is strongly controlled by location, i.e. the petrology of the source rocks of detrital grains. This supports the use of rutile as a well-suited tracer mineral for provenance studies. The results further suggest that (i) interpretations derived from whole-rock sediment geochemistry should be flanked by grain-size observations, and (ii) a more sound statistical evaluation of these interactions require the development of new tailor-made statistical tools to deal with such so-called two-way compositions
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A study of tin deposits from Priamurye (Russia) is performed to analyze the differences between them based on their origin and also on commercial criteria. A particular analysis based on their vertical zonality is also given for samples from Solnechnoe deposit. All the statistical analysis are made on the subcomposition formed by seven trace elements in cassiterite (In, Sc, Be, W, Nb, Ti and V) using the Aitchison’ methodology of analysis of compositional data
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The chemical composition of sediments and rocks, as well as their distribution at the Martian surface, represent a long term archive of processes, which have formed the planetary surface. A survey of chemical compositions by means of Compositional Data Analysis represents a valuable tool to extract direct evidence for weathering processes and allows to quantify weathering and sedimentation rates. clr-biplot techniques are applied for visualization of chemical relationships across the surface (“chemical maps”). The variability among individual suites of data is further analyzed by means of clr-PCA, in order to extract chemical alteration vectors between fresh rocks and their crusts and for an assessment of different source reservoirs accessible to soil formation. Both techniques are applied to elucidate the influence of remote weathering by combined analysis of several soil forming branches. Vector analysis in the Simplex provides the opportunity to study atmosphere surface interactions, including the role and composition of volcanic gases
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The application of Discriminant function analysis (DFA) is not a new idea in the study of tephrochrology. In this paper, DFA is applied to compositional datasets of two different types of tephras from Mountain Ruapehu in New Zealand and Mountain Rainier in USA. The canonical variables from the analysis are further investigated with a statistical methodology of change-point problems in order to gain a better understanding of the change in compositional pattern over time. Finally, a special case of segmented regression has been proposed to model both the time of change and the change in pattern. This model can be used to estimate the age for the unknown tephras using Bayesian statistical calibration
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Several eco-toxicological studies have shown that insectivorous mammals, due to their feeding habits, easily accumulate high amounts of pollutants in relation to other mammal species. To assess the bio-accumulation levels of toxic metals and their in°uence on essential metals, we quantified the concentration of 19 elements (Ca, K, Fe, B, P, S, Na, Al, Zn, Ba, Rb, Sr, Cu, Mn, Hg, Cd, Mo, Cr and Pb) in bones of 105 greater white-toothed shrews (Crocidura russula) from a polluted (Ebro Delta) and a control (Medas Islands) area. Since chemical contents of a bio-indicator are mainly compositional data, conventional statistical analyses currently used in eco-toxicology can give misleading results. Therefore, to improve the interpretation of the data obtained, we used statistical techniques for compositional data analysis to define groups of metals and to evaluate the relationships between them, from an inter-population viewpoint. Hypothesis testing on the adequate balance-coordinates allow us to confirm intuition based hypothesis and some previous results. The main statistical goal was to test equal means of balance-coordinates for the two defined populations. After checking normality, one-way ANOVA or Mann-Whitney tests were carried out for the inter-group balances
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Isotopic data are currently becoming an important source of information regarding sources, evolution and mixing processes of water in hydrogeologic systems. However, it is not clear how to treat with statistics the geochemical data and the isotopic data together. We propose to introduce the isotopic information as new parts, and apply compositional data analysis with the resulting increased composition. Results are equivalent to downscale the classical isotopic delta variables, because they are already relative (as needed in the compositional framework) and isotopic variations are almost always very small. This methodology is illustrated and tested with the study of the Llobregat River Basin (Barcelona, NE Spain), where it is shown that, though very small, isotopic variations comp lement geochemical principal components, and help in the better identification of pollution sources
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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
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In this paper we examine the problem of compositional data from a different starting point. Chemical compositional data, as used in provenance studies on archaeological materials, will be approached from the measurement theory. The results will show, in a very intuitive way that chemical data can only be treated by using the approach developed for compositional data. It will be shown that compositional data analysis is a particular case in projective geometry, when the projective coordinates are in the positive orthant, and they have the properties of logarithmic interval metrics. Moreover, it will be shown that this approach can be extended to a very large number of applications, including shape analysis. This will be exemplified with a case study in architecture of Early Christian churches dated back to the 5th-7th centuries AD
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Aquest projecte fi de carrera es centra en un restaurant fictici i genèric anomenat "El Restaurant al Punt". Es tractarà d' una empresa que s' inicia en el sector hostaler amb tot un seguit de coneixements previs per part dels propietaris. L' objectiu principal que es preten assolir en aquest projecte és: desenvolupar l' anàlisi, dissenyar i implementar una aplicació informàtica que permeti gestionar el funcionament d' un restaurant
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Peccata Mundi arrenca de la iniciativa del director de R+D+I de l'empresa Mas Parés, Jaume Juher, i l’artista plàstic Jaume Xifra, que l’any 2004 van decidir sumar a l’amistat que els uneix un objectiu: convergir en un sol projecte els reptes professionals que es plantejaven individualment des de cadascuna de les seves disciplines: l’art i la investigació gastronòmica. Posteriorment, a l'any 2005, s'incorporen al projecte els experts que constitueixen actualment el nucli central de treball: Josep Bel, expert en anàlisi sensorial i aplicació d'aromes; David Juher, matemàtic i professor de la UdG; Xavier de Palau, músic electrònic; Clara Perxachs, investigadora de la cultura del menjar; i Toni Botella, cuiner. A l'experiència gastronòmico-artística Peccata Mundi el participant tasta un seguit de plats i vins i valora les seves percepcions contestant un qüestionari. Les dades d'aquest qüestionari s'utilitzen, a través d'unes transformacions regides per criteris neurològics, matemàtics, antropològics, etc., per produir unes dades numèriques que seran l'entrada a una aplicació que les farà servir per generar un vídeo amb música d'una durada aproximadament de 2 minuts. Aquest vídeo, que consta d'imatges fractals en moviment i d'una música de fons, generada també utilitzant funcions de comportament caòtic, és el retrat audiovisual de l'experiència sensorial del participant. El projecte consisteix a implementar tota la logística informàtica de l’experiència sensorial Peccata Mundi: dissenyar les aplicacions d'entrada de dades, tractament de la base de dades, processament de les dades del qüestionari, generació del vídeo i la música i producció de l'arxiu audiovisual que finalment el participant s'emporta gravat en suport DVD
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En un nou escenari on la formació canvia l’enfocament des del formador cap a l’alumne i on l’aprenentatge s’orienta de manera més autònoma i reflexiva, les noves tecnologies de la informació i comunicació (TIC) ofereixen un ampli ventall de possibilitats per desenvolupar millores en els processos formatius. Un grup de professors del Departament d’Economia i Organització d’Empreses de la Universitat de Barcelona estan treballant en el disseny i la implantació de nous recursos i materials docents innovadors, emmarcats en l’ús de les TIC, tant com a suport de la docència presencial com per recolzar-hi l’aprenentatge autònom. En aquest sentit, l’objectiu de la present comunicació és presentar l’experiència del professorat que la subscriu en l’ús de mitjans digitals i multimèdia per a l’aprenentatge de diverses assignatures de l’àrea d’Organització d’Empreses