Plausibility regions on the skewness parameter of skew normal distributions based on inferential models
© 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 dist...
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| Main Authors: | , , , |
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| Format: | Book Series |
| Published: |
2018
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| Subjects: | |
| Online Access: | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85012887076&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/57129 |
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| Institution: | Chiang Mai University |
| Summary: | © 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. |
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