Analyzing Mean Profiles of Nonnormal Populations
Analyzing Mean Profiles of Nonnormal Populations
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DOI：
10.1080/03610926.2012.697970
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发表时间：
2014-08
期刊：
影响因子：
--
通讯作者：
Solomon W. Harrar;Jin Xu
中科院分区：
文献类型：
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作者：
Solomon W. Harrar;Jin Xu
当正态性的有效性未知且样本量适中时，我们考虑检验两个或多个总体的均值向量是否具有平行、重合或平坦的轮廓。利用多元矩的一些性质和矩阵运算，我们得到了Lawley-Hotelling统计量零分布的渐近展开式。我们也得到了相应的结果的情况下，兴趣在于重合和平坦性单独。所有的渐近展开近似的准确零分布的准确性，通过模拟检查。以一个林业试验的SO 4浓度剖面分析为例说明了该方法。
We consider testing whether the mean vectors of two or more populations have parallel, coincident, or flat profiles when the validity of normality is not known, and the sample sizes are moderate. Using some properties of multivariate moments and matrix manipulations, we obtain the asymptotic expansions for the null distribution of the Lawley–Hotelling statistics. We also derive the corresponding results in the situation where interest lies in coincidence and flatness alone. Accuracy of all the asymptotic expansions in approximating the exact null distributions is examined via simulation. Profile analysis of SO4 concentrations from a forestry experiment is used to illustrate the methods.