文章基本信息

标题：rTensor: An R Package for Multidimensional Array (Tensor) Unfolding, Multiplication, and Decomposition
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作者：James Li ; Jacob Bien ; Martin T. Wells 等
期刊名称：Journal of Statistical Software
印刷版ISSN：1548-7660
电子版ISSN：1548-7660
出版年度：2018
卷号：87
期号：1
页码：1-31
DOI：10.18637/jss.v087.i10
语种：English
出版社：University of California, Los Angeles
摘要：rTensor is an R package designed to provide a common set of operations and decompositions for multidimensional arrays (tensors). We provide an S4 class that wraps around the base 'array' class and overloads familiar operations to users of 'array', and we provide additional functionality for tensor operations that are becoming more relevant in recent literature. We also provide a general unfolding operation, for which the k-mode unfolding and the matrix vectorization are special cases of. Finally, package rTensor implements common tensor decompositions such as canonical polyadic decomposition, Tucker decomposition, multilinear principal component analysis, t-singular value decomposition, as well as related matrix-based algorithms such as generalized low rank approximation of matrices and popular value decomposition.
其他关键词：tensor;multidimensional arrays;S4;Tucker decomposition;multilinear principal components analysis;generalized low rank approximation of matrices;population valued decomposition;CANDECOMP/PARAFAC;tensor singular value decomposition