多个偏正态总体共同位置参数的Bootstrap置信区间

Abstract

Abstract:

In this paper, we consider the interval estimation and hypothesis testing problems for the common location parameter of several skew-normal populations when the scale parameters and skewness parameters are unknown. Firstly, we estimate the unknown parameters using the methods of moment estimation and maximum likelihood estimation. Secondly, the Bootstrap confidence intervals and Bootstrap test statistics are constructed, which generalize the results given by Xu [1] under several normal populations. Thirdly, the Monte Carlo simulation results indicate that the Bootstrap confidence intervals based on the methods of moment estimation and maximum penalized likelihood estimation perform better than other four confidence intervals. Finally, the above approaches are applied to the real data examples of regional gross domestic product of China and bioavailability in order to verify the reasonableness and effectiveness of the proposed approaches.

Key words: Skew-normal population, Common location parameter, Moment estimation, Maximum likelihood estimation, Bootstrap confidence interval

CLC Number:

O212

Rendao Ye,Zhongchi Wang,Kun Luo,Ya Lin. Bootstrap Confidence Intervals for the Common Location Parameter of Several Skew-Normal Populations[J].Acta mathematica scientia,Series A, 2021, 41(1): 194-216.

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References

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Bootstrap Confidence Intervals for the Common Location Parameter of Several Skew-Normal Populations

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