| dc.contributor | 應數系 | - |
| dc.creator (作者) | Nguyen, H.T. | - |
| dc.creator (作者) | 吳柏林 | zh_TW |
| dc.creator (作者) | Wu, Berlin | en_US |
| dc.date (日期) | 2006 | - |
| dc.date.accessioned | 21-Jul-2015 15:29:31 (UTC+8) | - |
| dc.date.available | 21-Jul-2015 15:29:31 (UTC+8) | - |
| dc.date.issued (上傳時間) | 21-Jul-2015 15:29:31 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/76762 | - |
| dc.description.abstract (摘要) | 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 (關聯) | Studies in Fuzziness and Soft Computing, 198, 129-144 | - |
| dc.title (題名) | Tests of hypothesis: Means | - |
| dc.type (資料類型) | article | en |
| dc.identifier.doi (DOI) | 10.1007/11353492_8 | - |
| dc.doi.uri (DOI) | http://dx.doi.org/10.1007/11353492_8 | - |
