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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Xiaonan Zhu | en_US |
| dc.contributor.author | Ziwei Ma | en_US |
| dc.contributor.author | Tonghui Wang | en_US |
| dc.contributor.author | Teerawut Teetranont | en_US |
| dc.date.accessioned | 2018-09-05T03:35:19Z | - |
| dc.date.available | 2018-09-05T03:35:19Z | - |
| dc.date.issued | 2017-02-01 | en_US |
| dc.identifier.issn | 1860949X | en_US |
| dc.identifier.other | 2-s2.0-85012887076 | en_US |
| dc.identifier.other | 10.1007/978-3-319-50742-2_16 | en_US |
| dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85012887076&origin=inward | en_US |
| dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/57129 | - |
| dc.description.abstract | © Springer International Publishing AG 2017. Inferential models (IMs) are new methods of statistical inference. They have several advantages: (1) They are free of prior distributions; (2) They rely on data. In this paper, 100(1 − α)% plausibility regions of the skewness parameter of skew-normal distributions are constructed by using IMs, which are the counterparts of classical confidence intervals in IMs. | en_US |
| dc.subject | Computer Science | en_US |
| dc.title | Plausibility regions on the skewness parameter of skew normal distributions based on inferential models | en_US |
| dc.type | Book Series | en_US |
| article.title.sourcetitle | Studies in Computational Intelligence | en_US |
| article.volume | 692 | en_US |
| article.stream.affiliations | New Mexico State University Las Cruces | en_US |
| article.stream.affiliations | Chiang Mai University | en_US |
| Appears in Collections: | CMUL: Journal Articles | |
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