Plausibility regions on the skewness parameter of skew normal distributions based on inferential models

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: Xiaonan Zhu, Ziwei Ma, Tonghui Wang, Teerawut Teetranont
Format: Book Series
Published: 2018
Subjects:
Computer Science
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
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spelling th-cmuir.6653943832-571292018-09-05T03:35:19Z Plausibility regions on the skewness parameter of skew normal distributions based on inferential models Xiaonan Zhu Ziwei Ma Tonghui Wang Teerawut Teetranont Computer Science © 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. 2018-09-05T03:35:19Z 2018-09-05T03:35:19Z 2017-02-01 Book Series 1860949X 2-s2.0-85012887076 10.1007/978-3-319-50742-2_16 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85012887076&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/57129
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Computer Science
spellingShingle Computer Science
Xiaonan Zhu
Ziwei Ma
Tonghui Wang
Teerawut Teetranont
Plausibility regions on the skewness parameter of skew normal distributions based on inferential models
description © 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.
format Book Series
author Xiaonan Zhu
Ziwei Ma
Tonghui Wang
Teerawut Teetranont
author_facet Xiaonan Zhu
Ziwei Ma
Tonghui Wang
Teerawut Teetranont
author_sort Xiaonan Zhu
title Plausibility regions on the skewness parameter of skew normal distributions based on inferential models
title_short Plausibility regions on the skewness parameter of skew normal distributions based on inferential models
title_full Plausibility regions on the skewness parameter of skew normal distributions based on inferential models
title_fullStr Plausibility regions on the skewness parameter of skew normal distributions based on inferential models
title_full_unstemmed Plausibility regions on the skewness parameter of skew normal distributions based on inferential models
title_sort plausibility regions on the skewness parameter of skew normal distributions based on inferential models
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85012887076&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/57129
_version_ 1681424821046476800

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