Abstract
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, \(100(1-\alpha )\%\) 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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The authors would like to thank referees for their valuable comments.
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Zhu, X., Ma, Z., Wang, T., Teetranont, T. (2017). Plausibility Regions on the Skewness Parameter of Skew Normal Distributions Based on Inferential Models. In: Kreinovich, V., Sriboonchitta, S., Huynh, VN. (eds) Robustness in Econometrics. Studies in Computational Intelligence, vol 692. Springer, Cham. https://doi.org/10.1007/978-3-319-50742-2_16
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DOI: https://doi.org/10.1007/978-3-319-50742-2_16
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