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A Simple but Efficient Approach for Testing Fuzzy Hypotheses

Authors
  • Parchami, Abbas1
  • Taheri, S. Mahmoud2
  • Gildeh, Bahram Sadeghpour3
  • Mashinchi, Mashaallah1
  • 1 Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Department of Statistics, Kerman, Iran , Kerman (Iran)
  • 2 College of Engineering, University of Tehran, Faculty of Engineering Science, Tehran, Iran , Tehran (Iran)
  • 3 Faculty of Mathematical Science, Ferdowsi University of Mashhad, Department of Statistics, Mashhad, Iran , Mashhad (Iran)
Type
Published Article
Journal
Journal of Uncertainty Analysis and Applications
Publisher
Springer Berlin Heidelberg
Publication Date
Jan 20, 2016
Volume
4
Issue
1
Identifiers
DOI: 10.1186/s40467-015-0042-8
Source
Springer Nature
Keywords
License
Green

Abstract

In this paper, a new method is proposed for testing fuzzy hypotheses based on the following two generalized p-values: (1) the generalized p-value of null fuzzy hypothesis against alternative fuzzy hypothesis and (2) the generalized p-value of alternative fuzzy hypothesis against null fuzzy hypothesis. In the proposed method, each generalized p-value is formulated on the basis of Zadeh’s probability measure of fuzzy events. The introduced p-value method has several advantages over the common p-value methods for testing fuzzy hypotheses. A few illustrative examples and also an agricultural example, based on a real-world data set, are given to clarify the proposed method.

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