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Bootstrap Inference on the Variance Component Functions in the Two-Way Random Effects Model with Interaction

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Abstract

In this paper, using the Bootstrap approach and generalized approach, the authors consider the one-sided hypothesis testing problems for variance component functions in the two-way random effects model. Firstly, the test statistics and confidence intervals for the sum of variance components are constructed. Next, the one-sided hypothesis testing problems for the ratio of variance components are also discussed. The Monte Carlo simulation results indicate that the Bootstrap approach is better than the generalized approach in most cases. Finally, the above approaches are applied to the real data examples of mice blood pH and molded plastic part’s dimensions.

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Author information

Authors and Affiliations

  1. School of Economics, Hangzhou Dianzi University, Hangzhou, 310018, China

    Rendao Ye & Wenting Ge

  2. Alibaba Business College, Hangzhou Normal University, Hangzhou, 310036, China

    Kun Luo

Authors
  1. Rendao Ye
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  2. Wenting Ge
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  3. Kun Luo
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Corresponding author

Correspondence to Rendao Ye.

Additional information

This research was supported by Zhejiang Provincial Natural Science Foundation of China under Grant No. LY20A010019, Ministry of Education of China, Humanities and Social Science Projects under Grant No. 19YJA910006, Fundamental Research Funds for the Provincial Universities of Zhejiang under Grant No. GK199900299012-204, Zhejiang Provincial Philosophy and Social Science Planning Zhijiang Youth Project of China under Grant No. 16ZJQN017YB, Zhejiang Provincial Statistical Science Research Base Project of China under Grant No. 19TJJD08, and Scientific Research and Innovation Foundation of Hangzhou Dianzi University under Grant No. CXJJ2019008.

This paper was recommended for publication by Editor TANG Niansheng.

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Ye, R., Ge, W. & Luo, K. Bootstrap Inference on the Variance Component Functions in the Two-Way Random Effects Model with Interaction. J Syst Sci Complex 34, 774–791 (2021). https://doi.org/10.1007/s11424-020-9216-7

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  • DOI: https://doi.org/10.1007/s11424-020-9216-7

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