Please use this identifier to cite or link to this item:
https://ah.lib.nccu.edu.tw/handle/140.119/76762
DC Field | Value | Language |
---|---|---|
dc.contributor | 應數系 | - |
dc.creator | Nguyen, H.T. | - |
dc.creator | 吳柏林 | zh_TW |
dc.creator | Wu, Berlin | en_US |
dc.date | 2006 | - |
dc.date.accessioned | 2015-07-21T07:29:31Z | - |
dc.date.available | 2015-07-21T07:29:31Z | - |
dc.date.issued | 2015-07-21T07:29:31Z | - |
dc.identifier.uri | http://nccur.lib.nccu.edu.tw/handle/140.119/76762 | - |
dc.description.abstract | In many expositions of fuzzy methods, fuzzy techniques are described as an alternative to a more traditional statistical approach. In this chapter, we present a class of fuzzy statistical decision processes in which hypothesis testing can be naturally reformulated in terms of interval-valued statistics. We provide the definitions of fuzzy mean, fuzzy distance as well as investigating their related properties. We also give some empirical examples to illustrate the techniques and to analyze fuzzy data. Empirical studies show that fuzzy hypothesis testing with soft computing for interval data are more realistic and reasonable in the social science research. © Springer-Verlag Berlin Heidelberg 2006. | - |
dc.format.extent | 176 bytes | - |
dc.format.mimetype | text/html | - |
dc.relation | Studies in Fuzziness and Soft Computing, 198, 129-144 | - |
dc.title | Tests of hypothesis: Means | - |
dc.type | article | en |
dc.identifier.doi | 10.1007/11353492_8 | - |
dc.doi.uri | http://dx.doi.org/10.1007/11353492_8 | - |
item.fulltext | With Fulltext | - |
item.openairetype | article | - |
item.cerifentitytype | Publications | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.grantfulltext | restricted | - |
Appears in Collections: | 期刊論文 |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
index.html | 176 B | HTML2 | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.