Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/76759
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dc.contributor應數系
dc.creatorNguyen, H.T.;Wu, Berlin
dc.creator吳柏林zh_TW
dc.date2006
dc.date.accessioned2015-07-21T07:29:26Z-
dc.date.available2015-07-21T07:29:26Z-
dc.date.issued2015-07-21T07:29:26Z-
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/76759-
dc.description.abstractWith the background in previous chapters, problems of statistical inference with fuzzy data should be somewhat straightforward in principle! By that we mean replacing random vectors by random fuzzy sets in all aspects of statistical inference. Of course, as in any generalization problem, this is just a guideline. Due to the nature of fuzzy data, as observations from random fuzzy sets, technical difficulties are expected in developing the theory. In fact, actual research is aiming at investigating, say, limit theorems for random fuzzy sets in order to provide rationale for large sample samples statistics with fuzzy data. © Springer-Verlag Berlin Heidelberg 2006.
dc.format.extent176 bytes-
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dc.relationStudies in Fuzziness and Soft Computing, 198, 45-70
dc.titleAspects of statistical inference
dc.typearticleen
dc.identifier.doi10.1007/11353492_5
dc.doi.urihttp://dx.doi.org/10.1007/11353492_5
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item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
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