12 resultados para Bayesian statistical decision theory

em Universitat de Girona, Spain


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Intra-urban inequalities in mortality have been infrequently analysed in European contexts. The aim of the present study was to analyse patterns of cancer mortality and their relationship with socioeconomic deprivation in small areas in 11 Spanish cities

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After publication of this work in 'International Journal of Health Geographics' on 13 january 2011 was wrong. The map of Barcelona in Figure two (figure 1 here) was reversed. The final correct Figure is presented here

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It has been shown that the accuracy of mammographic abnormality detection methods is strongly dependent on the breast tissue characteristics, where a dense breast drastically reduces detection sensitivity. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. Here, we describe the development of an automatic breast tissue classification methodology, which can be summarized in a number of distinct steps: 1) the segmentation of the breast area into fatty versus dense mammographic tissue; 2) the extraction of morphological and texture features from the segmented breast areas; and 3) the use of a Bayesian combination of a number of classifiers. The evaluation, based on a large number of cases from two different mammographic data sets, shows a strong correlation ( and 0.67 for the two data sets) between automatic and expert-based Breast Imaging Reporting and Data System mammographic density assessment

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The paper discusses maintenance challenges of organisations with a huge number of devices and proposes the use of probabilistic models to assist monitoring and maintenance planning. The proposal assumes connectivity of instruments to report relevant features for monitoring. Also, the existence of enough historical registers with diagnosed breakdowns is required to make probabilistic models reliable and useful for predictive maintenance strategies based on them. Regular Markov models based on estimated failure and repair rates are proposed to calculate the availability of the instruments and Dynamic Bayesian Networks are proposed to model cause-effect relationships to trigger predictive maintenance services based on the influence between observed features and previously documented diagnostics

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Compositional random vectors are fundamental tools in the Bayesian analysis of categorical data. Many of the issues that are discussed with reference to the statistical analysis of compositional data have a natural counterpart in the construction of a Bayesian statistical model for categorical data. This note builds on the idea of cross-fertilization of the two areas recommended by Aitchison (1986) in his seminal book on compositional data. Particular emphasis is put on the problem of what parameterization to use

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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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Aquesta tesi té la intenció de realitzar una contribució metodològica en el camp de la direcció estratègica, per mitjà de tres objectius: la revisió del concepte de risc ex post o realitzat per l'àmbit de la direcció estratègica; la concreció d'aquest concepte en una mesura de risc vàlida; i l'exploració de les possibilitats i l'interès de la descomposició del risc en diferents determinants que puguin explicar-ne la seva naturalesa. El primer objectiu es du a terme prenent com a base el concepte intuïtiu de risc i revisant la literatura en els camps més afins, especialment en la teoria comportamental de la decisió i la direcció estratègica. L'anàlisi porta a formular el risc ex post d'una activitat com el grau en què no s'han assolit els objectius per a aquesta activitat. La concreció d'aquesta definició al camp de la direcció estratègica implica que els objectius han de portar a l'obtenció de l'avantatge competitiu sostenible, el que descobreix l'interès de realitzar la mesura del risc a curt termini, és a dir, estàticament, i a llarg termini, és a dir, dinàmicament, pel que es defineix una mesura de Risc Estàtic i una altra de Risc dinàmic, respectivament. En l'anàlisi apareixen quatre dimensions conceptuals bàsiques a incorporar en les mesures: sign dependence, relativa, longitudinal i path dependence. Addicionalment, la consideració de que els resultats puguin ser cardinals o ordinals justifica que es formulin les dues mesures anteriors per a resultats cardinals i, en segon lloc, per a resultats ordinals. Les mesures de risc que es proposen sintetitzen els resultats ex post obtinguts en una mesura de centralitat relativa dels resultats, el Risc Estàtic, i una mesura de la tendència temporal dels resultats, el Risc Dinàmic. Aquesta proposta contrasta amb el plantejament tradicional dels models esperança-variància. Les mesures desenvolupades s'avaluen amb un sistema de propietats conceptuals i tècniques que s'elaboren expressament en la tesi i que permeten demostrar el seu gra de validesa i el de les mesures existents en la literatura, destacant els problemes de validesa d'aquestes darreres. També es proporciona un exemple teòric il·lustratiu de les mesures proposades que dóna suport a l'avaluació realitzada amb el sistema de propietats. Una contribució destacada d'aquesta tesi és la demostració de que les mesures de risc proposades permeten la descomposició additiva del risc si els resultats o diferencials de resultats es descomponen additivament. Finalment, la tesi inclou una aplicació de les mesures de Risc Estàtic i Dinàmic cardinals, així com de la seva descomposició, a l'anàlisi de la rendibilitat del sector bancari espanyol, en el període 1987-1999. L'aplicació il·lustra la capacitat de les mesures proposades per a analitzar la manifestació de l'avantatge competitiu, la seva evolució i naturalesa econòmica. En les conclusions es formulen possibles línees d'investigació futures.

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This paper sets out to identify the initial positions of the different decision makers who intervene in a group decision making process with a reduced number of actors, and to establish possible consensus paths between these actors. As a methodological support, it employs one of the most widely-known multicriteria decision techniques, namely, the Analytic Hierarchy Process (AHP). Assuming that the judgements elicited by the decision makers follow the so-called multiplicative model (Crawford and Williams, 1985; Altuzarra et al., 1997; Laininen and Hämäläinen, 2003) with log-normal errors and unknown variance, a Bayesian approach is used in the estimation of the relative priorities of the alternatives being compared. These priorities, estimated by way of the median of the posterior distribution and normalised in a distributive manner (priorities add up to one), are a clear example of compositional data that will be used in the search for consensus between the actors involved in the resolution of the problem through the use of Multidimensional Scaling tools

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The performance of the SAOP potential for the calculation of NMR chemical shifts was evaluated. SAOP results show considerable improvement with respect to previous potentials, like VWN or BP86, at least for the carbon, nitrogen, oxygen, and fluorine chemical shifts. Furthermore, a few NMR calculations carried out on third period atoms (S, P, and Cl) improved when using the SAOP potential

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First discussion on compositional data analysis is attributable to Karl Pearson, in 1897. However, notwithstanding the recent developments on algebraic structure of the simplex, more than twenty years after Aitchison’s idea of log-transformations of closed data, scientific literature is again full of statistical treatments of this type of data by using traditional methodologies. This is particularly true in environmental geochemistry where besides the problem of the closure, the spatial structure (dependence) of the data have to be considered. In this work we propose the use of log-contrast values, obtained by a simplicial principal component analysis, as LQGLFDWRUV of given environmental conditions. The investigation of the log-constrast frequency distributions allows pointing out the statistical laws able to generate the values and to govern their variability. The changes, if compared, for example, with the mean values of the random variables assumed as models, or other reference parameters, allow defining monitors to be used to assess the extent of possible environmental contamination. Case study on running and ground waters from Chiavenna Valley (Northern Italy) by using Na+, K+, Ca2+, Mg2+, HCO3-, SO4 2- and Cl- concentrations will be illustrated

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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

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This paper shows how instructors can use the problem‐based learning method to introduce producer theory and market structure in intermediate microeconomics courses. The paper proposes a framework where different decision problems are presented to students, who are asked to imagine that they are the managers of a firm who need to solve a problem in a particular business setting. In this setting, the instructors’ role is to provide both guidance to facilitate student learning and content knowledge on a just‐in‐time basis