Soft Methods in Probability, Statistics and Data Analysis edited by Przemyslaw Grzegorzewski, Olgierd Hryniewicz, Maria A. Gil.

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" approa...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Grzegorzewski, Przemyslaw (Editor), Hryniewicz, Olgierd (Editor), Gil, Maria A. (Editor)
Format: eBook
Language:English
Published: Heidelberg : Physica-Verlag HD : Imprint: Physica, 2002.
Edition:1st ed. 2002.
Series:Advances in Intelligent and Soft Computing, 16
Springer eBook Collection.
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Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.

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520 |a 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. 
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