Three-Way Principal Component Analysis with Its Applications to Psychology
Three-Way Principal Component Analysis with Its Applications to Psychology
复制标题
三因素主成分分析及其在心理学中的应用
DOI：
10.1007/978-4-431-55387-8_1
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
K. Adachi
中科院分区：
文献类型：
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作者：
K. Adachi
为分析三向数据而修改的主成分分析（PCA）程序通常被称为三向PCA（3WPCA）。流行的3WPCA程序被称为Tucker2，Tucker3和Parafac。我们描述了他们的模型和算法，强调Tucker2，Tucker3，Parafac和普通的双向PCA之间的层次关系。在介绍了Tucker3解的旋转技术后，用心理学中观察到的stimulisresponsepersperson数据说明了3WPCA程序。
The principal component analysis (PCA) procedures modified for analyzing three-way data are generally called three-way PCA (3WPCA). Popular 3WPCA procedures are known as the names, Tucker2, Tucker3, and Parafac. We describe their models and algorithms with an emphasis on a hierarchical relationship among Tucker2, Tucker3, Parafac, and the ordinary two-way PCA. After introducing the rotation techniques for Tucker3 solutions, 3WPCA procedures are illustrated with stimuliresponsespersons data observed in psychology.