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Soft Methods in Probability, Statistics and Data Analysis

  • Przemysław Grzegorzewski
  • Olgierd Hryniewicz
  • María Ángeles Gil

Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 16)

Table of contents

  1. Front Matter
    Pages I-X
  2. Introductory Papers

  3. Soft Methods in Probability: Fundamentals

    1. Front Matter
      Pages 63-63
    2. Andrew G. Bronevich, Alexander N. Karkishchenko
      Pages 76-83
    3. Andrew G. Bronevich, Alexander E. Lepskiy
      Pages 84-91
    4. Jaume Casasnovas, Francesc Rosselló
      Pages 92-97
    5. I. Cascos-Fernández, M. López-Díaz, M. A. Gil-Álvarez
      Pages 98-104
    6. Przemysław Grzegorzewski, Edyta Mrówka
      Pages 105-115
    7. Enrique Miranda, Inés Couso, Pedro Gil
      Pages 126-133
    8. Beloslav Riečan
      Pages 134-139
    9. Luis J. Rodríguez-Muñiz, Miguel López-Díaz, María Ángeles Gil
      Pages 140-145
    10. Matthias C. M. Troffaes, Gert de Cooman
      Pages 146-155
    11. Thomas Weiler, Ulrich Bodenhofer
      Pages 170-177
  4. Soft Methods in Statistics: Fuzzy Stochastic Models

    1. Front Matter
      Pages 187-187
    2. Jan van den Berg, Uzay Kaymak, Willem-Max van den Bergh
      Pages 189-196
    3. Przemysław Grzegorzewski
      Pages 197-206
    4. Mark Last, Abraham Kandel
      Pages 219-227
    5. M. Montenegro, A. Colubi, M. R. Casals, M. A. Gil-Álvarez
      Pages 228-235
    6. Andreas Wünsche
      Pages 236-243
  5. Soft Methods in Data Analysis: Fuzzy, Rough and Other Approaches

    1. Front Matter
      Pages 253-253
    2. Malay Bhattacharyya
      Pages 255-265
    3. Daniel Delic, Hans-J. Lenz, Mattis Neiling
      Pages 281-288
    4. Josep Domingo-Ferrer, Vicenç Torra
      Pages 289-294
    5. Andreas Faatz, Cornelia Seeberg, Ralf Steinmetz
      Pages 295-301
    6. Juliusz L. Kulikowski
      Pages 310-320
    7. Pedro Miranda, Michel Grabisch
      Pages 321-328
    8. Andrzej Skowron, Marcin S. Szczuka
      Pages 338-345
    9. Janusz Sobecki, Ngoc Thanh Nguyen
      Pages 346-354
    10. Aïda Valls, Vicenç Torra, Josep Domingo-Ferrer
      Pages 355-362

About these proceedings

Introduction

Classical probability theory and mathematical statistics appear sometimes too rigid for real life problems, especially while dealing with vague data or imprecise requirements. These problems have motivated many researchers to "soften" the classical theory. Some "softening" approaches utilize concepts and techniques developed in theories such as fuzzy sets theory, rough sets, possibility theory, theory of belief functions and imprecise probabilities, etc. Since interesting mathematical models and methods have been proposed in the frameworks of various theories, this text brings together experts representing different approaches used in soft probability, statistics and data analysis.

Keywords

Analysis Probability theory Stochastic model Stochastic models data analysis fuzzy mathematical statistics sets statistics

Editors and affiliations

  • Przemysław Grzegorzewski
    • 1
  • Olgierd Hryniewicz
    • 1
  • María Ángeles Gil
    • 2
  1. 1.Systems Research InstitutePolish Academy of SciencesWarsawPoland
  2. 2.Facultad de Ciencias, Departamento de Estadística e I.O. y D.M.Universidad de OviedoOviedoSpain

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-7908-1773-7
  • Copyright Information Physica-Verlag Heidelberg 2002
  • Publisher Name Physica, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-7908-1526-9
  • Online ISBN 978-3-7908-1773-7
  • Series Print ISSN 1867-5662
  • Series Online ISSN 1867-5670
  • Buy this book on publisher's site