文章基本信息

标题：Bootstrap Bartlett Adjustment on decomposed variance-covariance matrix of seemingly unrelated regression model
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作者：Oluwayemisi Oyeronke Alaba ; Afeez Abolaji Lawal
期刊名称：Afrika Statistika
印刷版ISSN：2316-090X
出版年度：2019
卷号：14
期号：1
页码：1891-1902
语种：English
出版社：African journals online
摘要：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.
关键词：Bartlett Adjustment;Bootstrap;Generalised Least Squares;Likeli- hood Ratio Test;Maximum Likelihood;Triangular Matrices;Seemingly Unrelated Regression