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Review Article

A parametric bootstrap approach for two-way error component regression models

, &
Pages 3952-3961 | Received 27 Jan 2015, Accepted 09 Jul 2015, Published online: 20 Dec 2016
 

ABSTRACT

In this article, the two-way error component regression model is considered. For the nonhomogenous linear hypothesis testing of regression coefficients, a parametric bootstrap (PB) approach is proposed. Simulation results indicate that the PB test, regardless of the sample sizes, maintains the Type I error rates very well and outperforms the existing generalized variable test, which may far exceed the intended significance level when the sample sizes are small or moderate. Real data examples illustrate the proposed approach work quite satisfactorily.

MATHEMATICS SUBJECT CLASSIFICATION:

Acknowledgments

The authors gratefully acknowledge the editor and referees for their valuable comments and suggestions that greatly improved the presentation of this article.

Funding

The research conducted in this article is supported by the Natural Science Foundation of Shanxi Province, China (2013011002-1).

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