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.

Version: 1.4.8
Depends: R (≥ 2.10.0)
Imports: methods
Published: 2021-05-15
Author: James Li and Jacob Bien and Martin Wells
Maintainer: Koki Tsuyuzaki <k.t.the-answer at hotmail.co.jp>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/rikenbit/rTensor
NeedsCompilation: no
Citation: rTensor citation info
Materials: NEWS
CRAN checks: rTensor results

Documentation:

Reference manual: rTensor.pdf

Downloads:

Package source: rTensor_1.4.8.tar.gz
Windows binaries: r-devel: rTensor_1.4.8.zip, r-release: rTensor_1.4.8.zip, r-oldrel: rTensor_1.4.8.zip
macOS binaries: r-release (arm64): rTensor_1.4.8.tgz, r-release (x86_64): rTensor_1.4.8.tgz, r-oldrel: rTensor_1.4.8.tgz
Old sources: rTensor archive

Reverse dependencies:

Reverse depends: tensorTS
Reverse imports: ccTensor, DelayedTensor, gcTensor, mwTensor, nnTensor, scITD, scTensor, SmoothTensor, TensorClustering, TRES, ttTensor

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