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Fuzzy E-Bayesian and Hierarchical Bayesian Estimations on the Kumaraswamy Distribution Using Censoring Data

Author

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  • Ramin Gholizadeh

    (Department of Statistics, University of Campinas (UNICAMP), Campinas, Brazil)

  • Manuel J.P. Barahona

    (Department of Statistics, Universidad del Bío-Bío, Concepcion, Chile)

  • Mastaneh Khalilpour

    (Payame Noor University, Amol, Iran)

Abstract

The main purpose of this paper is to provide a methodology for discussing the fuzzy. This approach will be used to create the fuzzy E-Bayesian and Hierarchical Bayesian estimations of Kumaraswamy Distribution under censoring data by introducing and applying a theorem called “Resolution Identity” for fuzzy sets. In other words, model parameters are assumed to be fuzzy random variables. The authors also use computational methods Wu (2003). For this purpose, the original problem is transformed into a nonlinear programming problem which is then divided up into four sub-problems to simplify computations. Finally, the results obtained for the sub-problems can be used to determine the membership functions of the fuzzy E-Bayesian and Hierarchical Bayesian estimations.

Suggested Citation

  • Ramin Gholizadeh & Manuel J.P. Barahona & Mastaneh Khalilpour, 2016. "Fuzzy E-Bayesian and Hierarchical Bayesian Estimations on the Kumaraswamy Distribution Using Censoring Data," International Journal of Fuzzy System Applications (IJFSA), IGI Global, vol. 5(2), pages 74-95, April.
    • Handle: RePEc:igg:jfsa00:v:5:y:2016:i:2:p:74-95
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