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Modelling series of studies with a common structure

机译:具有共同结构的一系列研究建模

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Consider the situation where the Structuration des Tableaux à Trois Indices de la Statistique (STATIS) methodology is applied to a series of studies, each study being represented by data and weight matrices. Relations between studies may be captured by the Hilbert–Schmidt product of these matrices. Specifically, the eigenvalues and eigenvectors of the Hilbert–Schmidt matrix S may be used to obtain a geometrical representation of the studies. The studies in a series may further be considered to have a common structure whenever their corresponding points lie along the first axis. The matrix S can be expressed as the sum of a rank 1 matrix λuuT with an error matrix E. Therefore, the components of the vector are sufficient to locate the points associated to the studies. Former models for S where vec(E) are mathematically tractable and yet do not take into account the symmetry of the matrix S. Thus a new symmetric model is proposed as well as the corresponding tests for a common structure. It is further shown how to assess the goodness of fit of such models. An application to the human immunodeficiency virus (HIV) infection is used for assessing the proposed model.
机译:考虑将统计数据构建为统计数据的统计方法(STATIS)应用于一系列研究的情况,每项研究均由数据和权重矩阵表示。这些矩阵的希尔伯特-施密特乘积可以捕获研究之间的关系。特别是,希尔伯特-施密特矩阵S的特征值和特征向量可用于获得研究的几何表示。每当它们的相应点沿第一轴放置时,一系列研究也可以被认为具有共同的结构。矩阵S可以表示为秩1矩阵λuuT与误差矩阵E的总和。因此,向量的分量足以定位与研究相关的点。 vec(E)在数学上易于控制,但未考虑矩阵S的对称性的S模型,因此,提出了一个新的对称模型以及对通用结构的相应测试。进一步显示了如何评估此类模型的拟合优度。一种针对人类免疫缺陷病毒(HIV)感染的应用程序用于评估所提出的模型。

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