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Credibility hypothesis testing of expectation of fuzzy normal distribution

机译:模糊正态分布期望值的可信度假设检验

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Identification of a suitable form for the membership function and assigning values for certain parameters in them while dealing with fuzzy environments is a challenging task in Credibility theory. Recently, Sampath and Ramya [15] considered a criterion called "membership ratio criterion" for testing the validity of a given hypothesis regarding the credibility distribution of a fuzzy variable against a rival hypothesis. A study on the application of the proposed criterion has been made with reference to the parameters involved in triangular credibility distributions. In this paper, a detailed study is made with reference to the fuzzy normal distribution. Test resulting from the application of membership ratio criterion for testing hypothesis about the expected value of the fuzzy normal distribution is considered assuming the variance of the distribution is known. Optimal properties of the derived tests are also studied.
机译:识别隶属函数的合适形式并在处理模糊环境时为其中的某些参数分配值是可信度理论中的一项艰巨任务。最近,Sampath和Ramya [15]考虑了一种称为“成员比率标准”的标准,用于测试关于模糊变量相对于竞争对手假设的可信度分布的给定假设的有效性。参照三角形可信度分布中涉及的参数,对所提出标准的应用进行了研究。本文针对模糊正态分布进行了详细研究。假设分布的方差是已知的,则可以考虑采用隶属比标准进行测试,以检验关于模糊正态分布的期望值的假设。还研究了衍生测试的最佳特性。

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