rTensor: Tools for Tensor Analysis and Decomposition

A set of tools for creation, manipulation, and modeling of tensors with arbitrary number of modes. A tensor in the context of data analysis is a multidimensional array. rTensor does this by providing a S4 class 'Tensor' that wraps around the base 'array' class. rTensor provides common tensor operations as methods, including matrix unfolding, summing/averaging across modes, calculating the Frobenius norm, and taking the inner product between two tensors. Familiar array operations are overloaded, such as index subsetting via '[' and element-wise operations. rTensor also implements various tensor decomposition, including CP, GLRAM, MPCA, PVD, and Tucker. For tensors with 3 modes, rTensor also implements transpose, t-product, and t-SVD, as defined in Kilmer et al. (2013). Some auxiliary functions include the Khatri-Rao product, Kronecker product, and the Hadamard product for a list of matrices.

Package details

AuthorJames Li and Jacob Bien and Martin Wells
MaintainerKoki Tsuyuzaki <k.t.the-answer@hotmail.co.jp>
LicenseGPL (>= 2)
URL https://github.com/rikenbit/rTensor
Package repositoryView on CRAN
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rTensor documentation built on May 15, 2021, 9:06 a.m.