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January 2019 Bootstrap Bartlett Adjustment on Decomposed Variance-Covariance Matrix of Seemingly Unrelated Regression Model
Oluwayemisi Oyeronke ALABA, Afeez Abolaji LAWAL
Afr. Stat. 14(1): 1891-1902 (January 2019). DOI: 10.16929/as/2019.1891.140


We investigated hypothesis testing in Seemingly Unrelated Regression (SUR) using Log Likelihood Ratio (LLR) test. The asymptotic distribution of this statistic is well documented in literature to have substantial inaccuracy by an order of magnitude leading to the rejection of too many true null hypotheses. Bartlett adjustment of Barndorff and Blaesild and Efron's bootstrap methods were considered to provide more accurate significance level to the distribution. Simulation results from the partitioned variance-covariance matrix showed that the lower triangular matrix performed better than the upper triangular matrix. The Bartlett method of Barndorff and Blaesild provided better significance value than the bootstrap method.

Ici, nous étudions des tests d'hypothèses dans une regression avec vraisemblance de non-correlation, basée le rapport du logarithme de la vraisemblance. La distribution asymptotique de la statistique utilisée est connue pour avoir une grande efficacité. Pour rémédier à cette situation, deux types dùajustement sont considerés : un base sur la méthode de Bartlett et un autre base sur la méthode de Barndorff et Blaesid. Une étude de simulation montre l'éfficacité des méthodes d'ajustement et la superiorité du second ajustement sur le premier.


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Oluwayemisi Oyeronke ALABA. Afeez Abolaji LAWAL. "Bootstrap Bartlett Adjustment on Decomposed Variance-Covariance Matrix of Seemingly Unrelated Regression Model." Afr. Stat. 14 (1) 1891 - 1902, January 2019.


Published: January 2019
First available in Project Euclid: 24 May 2019

zbMATH: 07058648
MathSciNet: MR3954229
Digital Object Identifier: 10.16929/as/2019.1891.140

Primary: 62F03 , 62J05

Keywords: Bartlett adjustment , bootstrap , generalised least squares , likelihood ratio test , maximum likelihood , seemingly unrelated regression , triangular matrices

Rights: Copyright © 2019 The Statistics and Probability African Society

Vol.14 • No. 1 • January 2019
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