Please use this identifier to cite or link to this item: https://ah.nccu.edu.tw/handle/140.119/61562


Title: Goodness-of-Fit Test for Membership Functions with Fuzzy Data
Authors: 吳柏林
Wu,Berlin
Contributors: 應數系
Keywords: Fuzzy set theory;Fuzzy numbers;Membership functions;Sampling survey;Chi-square test for goodness-of-fit
Date: 2012.1
Issue Date: 2013-11-11 11:41:36 (UTC+8)
Abstract: Conventionally, we use a chi-square test of homogeneity to determine whether the cell probabilities of a multinomial are equal. However, this process of testing hypotheses is based on the assumption of two-valued logic. If we collect questionnaire data using fuzzy logic, i.e., we record the category data with memberships instead of with a 0-1 type, then the conventional test of goodness-of- t will not work. In this paper, we present a new method, the fuzzy chi-square test, which will enable us to analyze those fuzzy sample data. The new testing process will efficiently solve the problem for which the category data are not integers. Some related properties of the fuzzy multinomial distribution are also described.
Relation: International Journal of Innovative Computing, Information and Control, 8(10) , 7437-7450
Data Type: article
Appears in Collections:[應用數學系] 期刊論文

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