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Bootstrap inference on the Behrens–Fisher-type problem for the skew-normal population under dependent samples

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  • Rendao Ye
  • Bingni Fang
  • Zhongchi Wang
  • Kun Luo
  • Wenting Ge

Abstract

In this article, the inference on location parameter for the skew-normal population under dependent samples is considered. First, the Bootstrap test statistics and Bootstrap confidence intervals for the Behrens–Fisher-type problem are constructed, respectively, when the scale parameter or skewness parameter is known. Second, the Monte-Carlo simulation results indicate that the Bootstrap approach is better than the approximate approach in most cases. Finally, the above approaches are illustrated by using the real data examples of gross domestic product and stock closing price.

Suggested Citation

  • Rendao Ye & Bingni Fang & Zhongchi Wang & Kun Luo & Wenting Ge, 2023. "Bootstrap inference on the Behrens–Fisher-type problem for the skew-normal population under dependent samples," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 52(11), pages 3751-3766, June.
    • Handle: RePEc:taf:lstaxx:v:52:y:2023:i:11:p:3751-3766
    DOI: 10.1080/03610926.2021.1980045
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