Detailed Information
Cited 0 time in 
Cited 0 time in 
Cited 0 time in
Metadata Downloads
The statistical inferences of fuzzy regression based on bootstrap techniques
Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Lee, Woo-Joo | - |
| dc.contributor.author | Jung, Hye Young | - |
| dc.contributor.author | Yoon, Jin Hee | - |
| dc.contributor.author | Choi, Seung Hoe | - |
| dc.date.accessioned | 2021-06-22T21:24:27Z | - |
| dc.date.available | 2021-06-22T21:24:27Z | - |
| dc.date.created | 2021-01-22 | - |
| dc.date.issued | 2015 | - |
| dc.identifier.issn | 1432-7643 | - |
| dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/20214 | - |
| dc.description.abstract | In this paper, we estimate the parameters of fuzzy regression models and investigate a statistical inferences with crisp inputs and fuzzy outputs for each α-cut. The proposed approaches of statistical inferences are fuzzy least squares (FLS) method and bootstrap technique. FLS is constructed on the basis of minimizing the sum of square of the total difference between observed and estimated outputs. Numerical examples are illustrated to perform the hypotheses test and to provide the percentile confidence regions by proposed approach. © 2014, Springer-Verlag Berlin Heidelberg. | - |
| dc.language | 영어 | - |
| dc.language.iso | en | - |
| dc.publisher | Springer Verlag | - |
| dc.title | The statistical inferences of fuzzy regression based on bootstrap techniques | - |
| dc.type | Article | - |
| dc.contributor.affiliatedAuthor | Jung, Hye Young | - |
| dc.identifier.doi | 10.1007/s00500-014-1415-5 | - |
| dc.identifier.scopusid | 2-s2.0-84924984229 | - |
| dc.identifier.wosid | 000351408300009 | - |
| dc.identifier.bibliographicCitation | Soft Computing, v.19, no.4, pp.883 - 890 | - |
| dc.relation.isPartOf | Soft Computing | - |
| dc.citation.title | Soft Computing | - |
| dc.citation.volume | 19 | - |
| dc.citation.number | 4 | - |
| dc.citation.startPage | 883 | - |
| dc.citation.endPage | 890 | - |
| dc.type.rims | ART | - |
| dc.type.docType | Article | - |
| dc.description.journalClass | 1 | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Computer Science | - |
| dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
| dc.relation.journalWebOfScienceCategory | Computer Science, Interdisciplinary Applications | - |
| dc.subject.keywordPlus | Regression analysis | - |
| dc.subject.keywordPlus | Statistical methods | - |
| dc.subject.keywordPlus | Bootstrap method | - |
| dc.subject.keywordPlus | Bootstrap technique | - |
| dc.subject.keywordPlus | Confidence region | - |
| dc.subject.keywordPlus | Fuzzy least-squares method | - |
| dc.subject.keywordPlus | Fuzzy regression models | - |
| dc.subject.keywordPlus | Fuzzy regressions | - |
| dc.subject.keywordPlus | Statistical inference | - |
| dc.subject.keywordPlus | Sum of squares | - |
| dc.subject.keywordPlus | Least squares approximations | - |
| dc.subject.keywordAuthor | Bootstrap method | - |
| dc.subject.keywordAuthor | Fuzzy least squares method | - |
| dc.subject.keywordAuthor | Fuzzy regression | - |
| dc.identifier.url | https://link.springer.com/article/10.1007/s00500-014-1415-5 | - |
- Files in This Item
- Go to Link
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
Related Researcher
- JUNG, HYE YOUNG
- ERICA 과학기술융합대학 (ERICA 수리데이터사이언스학과)