标题: 由混合变异建构基因表现分析之无母数检定
Nonparametric Test based on Combined Variation for Gene Expression Analysis
作者: 连紫汝
Lian, Tzu-Ju
陈邻安
Chen, Lin-An
统计学研究所
关键字: 基因表现分析;离群平均;离群和;t检定;Gene expression analysis;Outlier mean;Outlier sum;t-test
公开日期: 2010
摘要: 在致病基因的检测问题上,因为Tomlins et al.(2005)的发现使得探讨离群分配变成一个重要主题。不同于离群平均只能检测中心位置之改变,我们提出一个统计量它同时可以检测中心与离心两种变异。这个统计量还有一个好处。由它所建立的检定统计量不用估计未知分配的密度函数值。我们利用模拟分析比较了几种检定方法的检力并且做了比较。我们也进一步做了一个简单的实际资料分析。
Observed by Tomlins et al. (2005), detection of the shift for outlier-
distribution is a new topic useful in gene expression analysis. Alternative to the outlier mean test, we introduce a nonparametric statistic that can simultaneously detect the location shift and variation shift in the outlier distribution. There is an advantage, comparing with the outlier mean, that the test based on this statistic requires no prediction of distributional densities. Comparisons of this test statistic with some other methods in terms of mean square errors for estimation of their population parameters and powers for their abilities in detection of disease genes are simulated and displayed. Finally, a simple real data analysis is also performed and presented.
URI: http://140.113.39.130/cdrfb3/record/nctu/#GT079826507
http://hdl.handle.net/11536/47673
显示于类别:Thesis


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