Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/61556
DC FieldValueLanguage
dc.contributor應數系en_US
dc.creator吳柏林zh_TW
dc.creatorWu,Berlin-
dc.creatorYang,Chih Chingen_US
dc.date2012.06en_US
dc.date.accessioned2013-11-11T01:38:48Z-
dc.date.available2013-11-11T01:38:48Z-
dc.date.issued2013-11-11T01:38:48Z-
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/61556-
dc.description.abstractHow to evaluate an appropriate correlation with fuzzy data is an important topic in the economics especially when the data illustrate uncertain, inconsistent and incomplete type. Traditionally, we use Pearson`s Correlation Coefficient to measure the correlation between data with real value. However, when the data are composed of fuzzy numbers, it is not feasible to use such a traditional approach to determine the fuzzy correlation coefficient. This study proposes the calculation of fuzzy correlation with of fuzzy data: Interval, triangular and trapezoidal. Empirical studies are used to illustrate the application for evaluating fuzzy correlations. More related practical phenomena can be explained by this appropriate definition of fuzzy correlation.en_US
dc.format.extent408462 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoen_US-
dc.relationInternational Journal of Intelligent Technologies and Applied Statistics, 5(2), 109-120en_US
dc.subjectEvaluation ; Fuzzy data ; Psychometricsen_US
dc.titleA new approach on Correlation Evaluation with Fuzzy Data and its Applications in Econometricsen_US
dc.typearticleen
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
item.languageiso639-1en_US-
item.cerifentitytypePublications-
item.openairetypearticle-
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