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

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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 − 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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Zhu, X., Ma, Z., Wang, T., & Teetranont, T. (2017). Plausibility regions on the skewness parameter of skew normal distributions based on inferential models. In Studies in Computational Intelligence (Vol. 692, pp. 267–286). Springer Verlag. https://doi.org/10.1007/978-3-319-50742-2_16

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