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Log-Ratio and Parallel Factor Analysis: An Approach to Analyze Three-Way Compositional Data

机译:对数比和并行因子分析:一种分析三向成分数据的方法

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For the exploratory analysis of three-way data, Parafac/Candecomp model (CP) is one of the most applied models to study three-way arrays when the data are approximately trilinear. It is a three-way generalization of PCA (Principal Component Analysis). CP model is a common name for low-rank decomposition of three-way arrays. In this approach, the three-dimensional data are decomposed into a series of factors, each relating to one of the three physical ways. When the data are particular ratios, as in the case of compositional data, this model should consider the special problems that compositional data pose. The principal aim of this paper is to describe how an analysis of compositional data by CP is possible and how the results should be interpreted.
机译:对于三向数据的探索性分析,当数据近似为三线性时,Parafac / Candecomp模型(CP)是研究三向阵列的最常用模型之一。它是PCA(主成分分析)的三向概括。 CP模型是三向数组的低秩分解的通用名称。在这种方法中,三维数据被分解为一系列因素,每个因素都与三种物理方式中的一种有关。当数据是特定比例时,例如在组成数据的情况下,此模型应考虑组成数据带来的特殊问题。本文的主要目的是描述如何通过CP分析组成数据以及如何解释结果。

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