Advances in Intelligent and Soft Computing

Combining Soft Computing and Statistical Methods in Data Analysis

Editors: Borgelt, C., González Rodriguez, G., Trutschnig, W., Lubiano, M.A., Ángeles Gil, M., Grzegorzewski, P., Hryniewicz, O. (Eds.)

  • 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
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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.

Table of contents (78 chapters)

  • Prior Knowledge in the Classification of Biomedical Data

    Abbate, Danilo (et al.)

    Pages 1-8

  • Estimation of a Simple Genetic Algorithm Applied to a Laboratory Experiment

    Alfarano, Simone (et al.)

    Pages 9-16

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

    Alfons, Andreas (et al.)

    Pages 17-24

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

    Ayala, Guillermo

    Pages 25-31

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

    Blanco-Fernández, Angela (et al.)

    Pages 33-40

Buy this book

eBook $389.00
price for USA
  • ISBN 978-3-642-14746-3
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $499.00
price for USA
  • ISBN 978-3-642-14745-6
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Combining Soft Computing and Statistical Methods in Data Analysis
Editors
  • Christian Borgelt
  • Gil González Rodriguez
  • Wolfgang Trutschnig
  • María Asunción Lubiano
  • María Ángeles Gil
  • Przemyslaw Grzegorzewski
  • Olgierd Hryniewicz
Series Title
Advances in Intelligent and Soft Computing
Series Volume
77
Copyright
2010
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer Berlin Heidelberg
eBook ISBN
978-3-642-14746-3
DOI
10.1007/978-3-642-14746-3
Softcover ISBN
978-3-642-14745-6
Series ISSN
1867-5662
Edition Number
1
Number of Pages
XVIII, 644
Number of Illustrations and Tables
96 b/w illustrations
Topics