Clustering compositional data trajectories

Our essay aims at studying suitable statistical methods for the clustering of compositional data in situations where observations are constituted by trajectories of compositional data, that is, by sequences of composition measurements along a domain. Observed trajectories are known as “functional data” and several methods have been proposed for their analysis. In particular, methods for clustering functional data, known as Functional Cluster Analysis (FCA), have been applied by practitioners and scientists in many fields. To our knowledge, FCA techniques have not been extended to cope with the problem of clustering compositional data trajectories. In order to extend FCA techniques to the analysis of compositional data, FCA clustering techniques have to be adapted by using a suitable compositional algebra. The present work centres on the following question: given a sample of compositional data trajectories, how can we formulate a segmentation procedure giving homogeneous classes? To address this problem we follow the steps described below. First of all we adapt the well-known spline smoothing techniques in order to cope with the smoothing of compositional data trajectories. In fact, an observed curve can be thought of as the sum of a smooth part plus some noise due to measurement errors. Spline smoothing techniques are used to isolate the smooth part of the trajectory: clustering algorithms are then applied to these smooth curves. The second step consists in building suitable metrics for measuring the dissimilarity between trajectories: we propose a metric that accounts for difference in both shape and level, and a metric accounting for differences in shape only. A simulation study is performed in order to evaluate the proposed methodologies, using both hierarchical and partitional clustering algorithm. The quality of the obtained results is assessed by means of several indices

Comparing methods for dimensionality reduction when data are density functions

Functional Data Analysis (FDA) deals with samples where a whole function is observed for each individual. A particular case of FDA is when the observed functions are density functions, that are also an example of infinite dimensional compositional data. In this work we compare several methods for dimensionality reduction for this particular type of data: functional principal components analysis (PCA) with or without a previous data transformation and multidimensional scaling (MDS) for diferent inter-densities distances, one of them taking into account the compositional nature of density functions. The difeerent methods are applied to both artificial and real data (households income distributions)

Dynamic graphics of parametrically linked multivariate methods used in compositional data analysis

Many multivariate methods that are apparently distinct can be linked by introducing one or more parameters in their definition. Methods that can be linked in this way are correspondence analysis, unweighted or weighted logratio analysis (the latter also known as "spectral mapping"), nonsymmetric correspondence analysis, principal component analysis (with and without logarithmic transformation of the data) and multidimensional scaling. In this presentation I will show how several of these methods, which are frequently used in compositional data analysis, may be linked through parametrizations such as power transformations, linear transformations and convex linear combinations. Since the methods of interest here all lead to visual maps of data, a "movie" can be made where where the linking parameter is allowed to vary in small steps: the results are recalculated "frame by frame" and one can see the smooth change from one method to another. Several of these "movies" will be shown, giving a deeper insight into the similarities and differences between these methods

Statistical treatment of grain-size curves and empirical distributions: densities as compositions?

The preceding two editions of CoDaWork included talks on the possible consideration of densities as infinite compositions: Egozcue and D´ıaz-Barrero (2003) extended the Euclidean structure of the simplex to a Hilbert space structure of the set of densities within a bounded interval, and van den Boogaart (2005) generalized this to the set of densities bounded by an arbitrary reference density. From the many variations of the Hilbert structures available, we work with three cases. For bounded variables, a basis derived from Legendre polynomials is used. For variables with a lower bound, we standardize them with respect to an exponential distribution and express their densities as coordinates in a basis derived from Laguerre polynomials. Finally, for unbounded variables, a normal distribution is used as reference, and coordinates are obtained with respect to a Hermite-polynomials-based basis. To get the coordinates, several approaches can be considered. A numerical accuracy problem occurs if one estimates the coordinates directly by using discretized scalar products. Thus we propose to use a weighted linear regression approach, where all k- order polynomials are used as predictand variables and weights are proportional to the reference density. Finally, for the case of 2-order Hermite polinomials (normal reference) and 1-order Laguerre polinomials (exponential), one can also derive the coordinates from their relationships to the classical mean and variance. Apart of these theoretical issues, this contribution focuses on the application of this theory to two main problems in sedimentary geology: the comparison of several grain size distributions, and the comparison among different rocks of the empirical distribution of a property measured on a batch of individual grains from the same rock or sediment, like their composition

Revisiting the compositional data. Some fundamental questions and new prospects in Archaeometry and Archaeology

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

Modelling of Mercury’s surface composition and remote detection from the orbit with the BepiColombo Mercury Planetary Orbiter

It can be assumed that the composition of Mercury’s thin gas envelope (exosphere) is related to the composition of the planets crustal materials. If this relationship is true, then inferences regarding the bulk chemistry of the planet might be made from a thorough exospheric study. The most vexing of all unsolved problems is the uncertainty in the source of each component. Historically, it has been believed that H and He come primarily from the solar wind, while Na and K originate from volatilized materials partitioned between Mercury’s crust and meteoritic impactors. The processes that eject atoms and molecules into the exosphere of Mercury are generally considered to be thermal vaporization, photonstimulated desorption (PSD), impact vaporization, and ion sputtering. Each of these processes has its own temporal and spatial dependence. The exosphere is strongly influenced by Mercury’s highly elliptical orbit and rapid orbital speed. As a consequence the surface undergoes large fluctuations in temperature and experiences differences of insolation with longitude. We will discuss these processes but focus more on the expected surface composition and solar wind particle sputtering which releases material like Ca and other elements from the surface minerals and discuss the relevance of composition modelling

Vertebrates Limb Geometry in the Simplex space

A novel metric comparison of the appendicular skeleton (fore and hind limb) of different vertebrates using the Compositional Data Analysis (CDA) methodological approach it’s presented. 355 specimens belonging in various taxa of Dinosauria (Sauropodomorpha, Theropoda, Ornithischia and Aves) and Mammalia (Prothotheria, Metatheria and Eutheria) were analyzed with CDA. A special focus has been put on Sauropodomorpha dinosaurs and the Aitchinson distance has been used as a measure of disparity in limb elements proportions to infer some aspects of functional morphology

Robust Factor Analysis for Compositional Data

Factor analysis as frequent technique for multivariate data inspection is widely used also for compositional data analysis. The usual way is to use a centered logratio (clr) transformation to obtain the random vector y of dimension D. The factor model is then y = Λf + e (1) with the factors f of dimension k < D, the error term e, and the loadings matrix Λ. Using the usual model assumptions (see, e.g., Basilevsky, 1994), the factor analysis model (1) can be written as Cov(y) = ΛΛT + ψ (2) where ψ = Cov(e) has a diagonal form. The diagonal elements of ψ as well as the loadings matrix Λ are estimated from an estimation of Cov(y). Given observed clr transformed data Y as realizations of the random vector y. Outliers or deviations from the idealized model assumptions of factor analysis can severely effect the parameter estimation. As a way out, robust estimation of the covariance matrix of Y will lead to robust estimates of Λ and ψ in (2), see Pison et al. (2003). Well known robust covariance estimators with good statistical properties, like the MCD or the S-estimators (see, e.g. Maronna et al., 2006), rely on a full-rank data matrix Y which is not the case for clr transformed data (see, e.g., Aitchison, 1986). The isometric logratio (ilr) transformation (Egozcue et al., 2003) solves this singularity problem. The data matrix Y is transformed to a matrix Z by using an orthonormal basis of lower dimension. Using the ilr transformed data, a robust covariance matrix C(Z) can be estimated. The result can be back-transformed to the clr space by C(Y ) = V C(Z)V T where the matrix V with orthonormal columns comes from the relation between the clr and the ilr transformation. Now the parameters in the model (2) can be estimated (Basilevsky, 1994) and the results have a direct interpretation since the links to the original variables are still preserved. The above procedure will be applied to data from geochemistry. Our special interest is on comparing the results with those of Reimann et al. (2002) for the Kola project data

Experimental design on the simplex

Optimum experimental designs depend on the design criterion, the model and the design region. The talk will consider the design of experiments for regression models in which there is a single response with the explanatory variables lying in a simplex. One example is experiments on various compositions of glass such as those considered by Martin, Bursnall, and Stillman (2001). Because of the highly symmetric nature of the simplex, the class of models that are of interest, typically Scheff´e polynomials (Scheff´e 1958) are rather different from those of standard regression analysis. The optimum designs are also rather different, inheriting a high degree of symmetry from the models. In the talk I will hope to discuss a variety of modes for such experiments. Then I will discuss constrained mixture experiments, when not all the simplex is available for experimentation. Other important aspects include mixture experiments with extra non-mixture factors and the blocking of mixture experiments. Much of the material is in Chapter 16 of Atkinson, Donev, and Tobias (2007). If time and my research allows, I would hope to finish with a few comments on design when the responses, rather than the explanatory variables, lie in a simplex. References Atkinson, A. C., A. N. Donev, and R. D. Tobias (2007). Optimum Experimental Designs, with SAS. Oxford: Oxford University Press. Martin, R. J., M. C. Bursnall, and E. C. Stillman (2001). Further results on optimal and efficient designs for constrained mixture experiments. In A. C. Atkinson, B. Bogacka, and A. Zhigljavsky (Eds.), Optimal Design 2000, pp. 225–239. Dordrecht: Kluwer. Scheff´e, H. (1958). Experiments with mixtures. Journal of the Royal Statistical Society, Ser. B 20, 344–360. 1

Gestió i tractament d’aigües residuals [versió html]

Sota el títol Gestió i tractament d’aigües residuals trobem un llibre que pretén ser una guia útil per a la comunitat que es mou a l’entorn de la gestió i tractament d’aigües residuals. El document es troba estructurat en 5 capítols, el primer dels quals és una presentació de la problemàtica associada a les aigües residuals, així com de les possibles actuacions a portar a terme per a solucionar aquesta qüestió. Ja entrant en la matèria trobem els capítols 2 i 3 on es descriu en detall el sistema de clavegueram i les diferents tecnologies de depuració disponibles. No més important que el disseny d’un sistema de sanejament, és la seva gestió, i per aquest motiu en el capítol 4 s’hi recullen les pautes bàsiques d’operació i manteniment. Finalment, el darrer dels capítols contempla el destí final de les aigües ja depurades: el medi receptor o bé la reutilització d’aquestes

Anglès i el seu emblemàtic Barri Antic. Model per a l’estudi de l’interpretació del territori en el marc de les Vies Verdes

Aquest projecte parteix d’inici de tres objectius fonamentals, com són: estudiar a fons el Barri Antic d’Anglès, posteriorment dur a terme una interpretació rigorosa i objectiva d’aquest Casc Antic i finalment demostrar el gran potencial que atresoren les Vies Verdes de Girona

Avaluació dels aprenentatges en les innovacions docents dels estudis de biologia de la Universitat Pompeu Fabra

Els organitzadors de les Jornades de Treball sobre L’Avaluació dels Aprenentatges a partir de Competències ens van invitar a explicar l’experiència d’avaluació de les innovacions docents que s’estan desenvolupant als estudis de Biologia de la Universitat Pompeu Fabra (UPF) en la seva adaptació a l’espai europeu d’educació superior (EEES). Aquest escrit pretén resumir la nostra experiència i destacar els elements que considerem més rellevants. En primer lloc resumirem les característiques del projecte educatiu i d’avaluació de la Facultat de Ciències de la Salut i de la Vida (FCSV) de la UPF, centre on es desenvolupa l’experiència. Posteriorment descriurem la nostra experiència d’avaluació de les innovacions docents i, finalment, en farem una valoració i destacarem els problemes principals

Docència: L'adaptació a l'espai europeu d'educació superior a l'Escola Politècnica Superior

L’Escola Politècnica Superior va iniciar el seu camí cap a l’adaptació a l’espai europeu d’educació superior durant el curs 2004-2005 participant en el Pla pilot de les universitats catalanes d’adaptació a l’espai europeu d’educació superior, projecte finançat per l’Agència per a la Qualitat del Sistema Universitari de Catalunya (AQU)

Recerca i transferència tecnològica: Tres grups de recerca de l'Escola Politècnica Superior expliquen algunes de les seves línies de recerca

El Laboratori de Gràfics i Imatge (GILab) és un grup de recerca de la Universitat de Girona, dirigit pel Dr. Mateu Sbert, i que està adscrit a l'Institut d'Informàtica i Aplicacions i a l'Institut d'Investigació Biomèdica de Girona. Està format per 6 doctors, 8 estudiants de doctorat i un nombre important d'estudiants en formació que col•laboren en diversos projectes. La recerca i transferència del grup es desenvolupen principalment en els camps d'informàtica gràfica i processament d'imatge

Professionals: L'experiència d'un titulat que desenvolupa la seva activitat professional dissenyant circuits electrònics

Seguint amb l’objectiu que titulats a l’Escola Politècnica Superior expliquin detalls de la seva inserció laboral i del seu perfil professional, en aquest segon número de la revista entrevistem el Sr. Albert Pijuan Vila. En aquest cas no es tracta d’un titulat recent, ja que l’Albert va finalitzar els estudis l’any 1988. Recordem que, si bé al 1988 ja disposàvem de d’actual edifici P-I de l’EPS, l’escola encara estava vinculada a la Universitat Politècnica de Catalunya. El principal interès que ens ha mogut a entrevistar l’Albert ha estat el fet de poder presentar les característiques d’un tipus de lloc de treball que pot ser adient per a alguns dels titulats actuals de l’EPS, especialment d’Enginyeria Tècnica Industrial, especialitat Electrònica Industrial i Enginyeria Tècnica en Informàtica de Sistemes. L’entrevista també vol explorar quins són els tipus de coneixements i les competències que haurien d’adquirir els estudiants per adequar-se millor a aquest tipus de sortida professional