Soft Methods for Handling Variability and Imprecision

  • Didier Dubois
  • M. Asunción Lubiano
  • Henri Prade
  • María Ángeles Gil
  • Przemysław Grzegorzewski
  • Olgierd Hryniewicz

Part of the Advances in Soft Computing book series (AINSC, volume 48)

Table of contents

  1. Front Matter
  2. Invited Papers

  3. Foundations

    1. Front Matter
      Pages 33-33
    2. Jonathan Lawry, Yongchuan Tang
      Pages 35-42
    3. Marco E. G. V. Cattaneo
      Pages 43-50
    4. Giulianella Coletti, Romano Scozzafava, Barbara Vantaggi
      Pages 51-58
    5. Andrew Schumann
      Pages 59-65
    6. Sébastien Destercke, Gert de Cooman
      Pages 66-73
  4. Statistical Methods

    1. Front Matter
      Pages 81-81
    2. Statistical Inference

    3. Statistical Tests

      1. Ángela Blanco, Ana Colubi, Norberto Corral, Gil González-Rodríguez
        Pages 111-117
      2. Inés Couso, Luciano Sánchez
        Pages 126-132

About these proceedings


Probability theory has been the only well-founded theory of uncertainty for a long time. It was viewed either as a powerful tool for modelling random phenomena, or as a rational approach to the notion of degree of belief. During the last thirty years, in areas centered around decision theory, artificial intelligence and information processing, numerous approaches extending or orthogonal to the existing theory of probability and mathematical statistics have come to the front. The common feature of those attempts is to allow for softer or wider frameworks for taking into account the incompleteness or imprecision of information. Many of these approaches come down to blending interval or fuzzy interval analysis with probabilistic methods.

This book gathers contributions to the 4th International Conference on Soft methods in Probability and Statistics. Its aim is to present recent results illustrating such new trends that enlarge the statistical and uncertainty modeling traditions, towards the handling of incomplete or subjective information. It covers a broad scope ranging from philosophical and mathematical underpinnings of new uncertainty theories, with a stress on their impact in the area of statistics and data analysis, to numerical methods and applications to environmental risk analysis and mechanical engineering. A unique feature of this collection is to establish a dialogue between fuzzy random variables and imprecise probability theories.


Bayesian inference Binomial distribution Cyc Imprecise probability Measure Probability theory Random variable Revision artificial intelligence decision theory information processing modeling optimization semantics uncertainty

Editors and affiliations

  • Didier Dubois
    • 1
  • M. Asunción Lubiano
    • 2
  • Henri Prade
    • 1
  • María Ángeles Gil
    • 2
  • Przemysław Grzegorzewski
    • 3
  • Olgierd Hryniewicz
    • 4
  1. 1.Université Paul SabatierToulouseFrance
  2. 2.Universidad de OviedoSpain
  3. 3.Polish Academy of SciencesWarsawPoland
  4. 4.Polish Academy of Sciences,WarsawPoland

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2008
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-85026-7
  • Online ISBN 978-3-540-85027-4
  • Series Print ISSN 1615-3871
  • Series Online ISSN 1860-0794
  • About this book