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Combining Soft Computing and Statistical Methods in Data Analysis

  • Conference proceedings
  • © 2010

Overview

Editors:
  1. Christian Borgelt

    1. Research Unit on Intelligent Data Analysis and Graphical Models, European Centre for Soft Computing Edificio Científico-Tecnológico. 3a Planta, Mieres, Spain

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  2. Gil González-Rodríguez

    1. Research Unit on Intelligent Data Analysis and Graphical Models, European Centre for Soft Computing Edificio Científico-Tecnológico. 3a Planta, Mieres, Spain

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  3. Wolfgang Trutschnig

    1. Research Unit on Intelligent Data Analysis and Graphical Models, European Centre for Soft Computing Edificio Científico-Tecnológico. 3a Planta, Mieres, Spain

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  4. María Asunción Lubiano

    1. Departamento de Estadística e I.O. y D.M., Universidad de Oviedo, Facultad de Ciencias, Oviedo, Spain

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  5. María Ángeles Gil

    1. Departamento de Estadística e I.O. yD.M., Universidad de Oviedo, Facultad de Ciencias, Oviedo, Spain

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  6. Przemysław Grzegorzewski

    1. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

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  7. Olgierd Hryniewicz

    1. Systems Research Institute, Polish Academy of Science, Warsaw, Poland

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  • Recent research on Soft Methods in Probability and Statistics
  • Results of the 5th International Conference on Soft Methods in Probability and Statistics (SMPS'2010) held in Oviedo and Mieres , Asturias, Spain at September 28-October 1, 2010
  • Written by a leading expert in the field

Part of the book series: Advances in Intelligent and Soft Computing (AINSC, volume 77)

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About this book

Over the last forty years there has been a growing interest to extend probability theory and statistics and to allow for more flexible modelling of imprecision, uncertainty, vagueness and ignorance. The fact that in many real-life situations data uncertainty is not only present in the form of randomness (stochastic uncertainty) but also in the form of imprecision/fuzziness is but one point underlining the need for a widening of statistical tools. Most such extensions originate in a "softening" of classical methods, allowing, in particular, to work with imprecise or vague data, considering imprecise or generalized probabilities and fuzzy events, etc. About ten years ago the idea of establishing a recurrent forum for discussing new trends in the before-mentioned context was born and resulted in the first International Conference on Soft Methods in Probability and Statistics (SMPS) that was held in Warsaw in 2002. In the following years the conference took place in Oviedo (2004), in Bristol (2006) and in Toulouse (2008). In the current edition the conference returns to Oviedo. This edited volume is a collection of papers presented at the SMPS 2010 conference held in Mieres and Oviedo. It gives a comprehensive overview of current research into the fusion of soft methods with probability and statistics.

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Keywords

Table of contents (78 papers)

  1. Front Matter

    Download chapter PDF

  2. Prior Knowledge in the Classification of Biomedical Data

    • Danilo Abbate, Roberta De Asmundis, Mario Rosario Guarracino
    Pages 1-8

  3. Estimation of a Simple Genetic Algorithm Applied to a Laboratory Experiment

    • Simone Alfarano, Eva Camacho, Josep Domenech
    Pages 9-16

  4. A Comparison of Robust Methods for Pareto Tail Modeling in the Case of Laeken Indicators

    • Andreas Alfons, Matthias Templ, Peter Filzmoser, Josef Holzer
    Pages 17-24

  5. R Code for Hausdorff and Simplex Dispersion Orderings in the 2D Case

    • Guillermo Ayala
    Pages 25-31

  6. On Some Confidence Regions to Estimate a Linear Regression Model for Interval Data

    • Angela Blanco-Fernández, Norberto Corral, Gil González-Rodríguez, Antonio Palacio
    Pages 33-40

  7. Possibilistic Coding: Error Detection vs. Error Correction

    • Luca Bortolussi, Andrea Sgarro
    Pages 41-48

  8. Coherent Correction for Conditional Probability Assessments with R

    • A. Brozzi, A. Morelli, F. Vattari
    Pages 49-56

  9. Inferential Rules for Weak Graphoid

    • Giuseppe Busanello, Barbara Vantaggi
    Pages 57-64

  10. Fast Factorization of Probability Trees and Its Application to Recursive Trees Learning

    • Andrés Cano, Manuel Gómez-Olmedo, Cora B. Pérez-Ariza, Antonio Salmerón
    Pages 65-72

  11. Option Pricing in Incomplete Markets Based on Partial Information

    • Andrea Capotorti, Giuliana Regoli, Francesca Vattari
    Pages 73-80

  12. Lorenz Curves of extrema

    • Ignacio Cascos, Miguel Mendes
    Pages 81-88

  13. Likelihood in a Possibilistic and Probabilistic Context: A Comparison

    • Giulianella Coletti, Davide Petturiti, Barbara Vantaggi
    Pages 89-96

  14. Nonparametric Predictive Inference for Order Statistics of Future Observations

    • Frank P. A. Coolen, Tahani A. Maturi
    Pages 97-104

  15. Expected Pair-Wise Comparison of the Outcomes of a Fuzzy Random Variable

    • Inés Couso, Laura Garrido, Susana Montes, Luciano Sánchez
    Pages 105-113

  16. The Behavioral Meaning of the Median

    • Inés Couso, Luciano Sánchez
    Pages 115-122

  17. Functional Classification and the Random Tukey Depth. Practical Issues

    • Juan A. Cuesta-Albertos, Alicia Nieto-Reyes
    Pages 123-130

  18. On Concordance Measures and Copulas with Fractal Support

    • E. de Amo, M. Díaz Carrillo, J. Fernández-Sánchez
    Pages 131-138

  19. Factorisation Properties of the Strong Product

    • Gert de Cooman, Enrique Miranda, Marco Zaffalon
    Pages 139-147

  20. Hadamard Majorants for the Convex Order and Applications

    • Jesús de la Cal, Javier Cárcamo, Luis Escauriaza
    Pages 149-154
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Editors and Affiliations

  • Research Unit on Intelligent Data Analysis and Graphical Models, European Centre for Soft Computing Edificio Científico-Tecnológico. 3a Planta, Mieres, Spain

    Christian Borgelt, Gil González-Rodríguez, Wolfgang Trutschnig

  • Departamento de Estadística e I.O. y D.M., Universidad de Oviedo, Facultad de Ciencias, Oviedo, Spain

    María Asunción Lubiano

  • Departamento de Estadística e I.O. yD.M., Universidad de Oviedo, Facultad de Ciencias, Oviedo, Spain

    María Ángeles Gil

  • Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Przemysław Grzegorzewski

  • Systems Research Institute, Polish Academy of Science, Warsaw, Poland

    Olgierd Hryniewicz

Bibliographic Information

  • Book Title: Combining Soft Computing and Statistical Methods in Data Analysis

  • Editors: Christian Borgelt, Gil González-Rodríguez, Wolfgang Trutschnig, María Asunción Lubiano, María Ángeles Gil, Przemysław Grzegorzewski, Olgierd Hryniewicz

  • Series Title: Advances in Intelligent and Soft Computing

  • DOI: https://doi.org/10.1007/978-3-642-14746-3

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer Berlin Heidelberg 2010

  • Softcover ISBN: 978-3-642-14745-6Published: 11 August 2010

  • eBook ISBN: 978-3-642-14746-3Published: 12 October 2010

  • Series ISSN: 1867-5662

  • Series E-ISSN: 1867-5670

  • Edition Number: 1

  • Number of Pages: XVIII, 644

  • Number of Illustrations: 96 b/w illustrations

  • Topics: Computational Intelligence

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