rTensor: Tools for Tensor Analysis and Decomposition (original) (raw)
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 |
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| Depends: | R (≥ 2.10.0) |
| Imports: | methods |
| Published: | 2021-05-15 |
| DOI: | 10.32614/CRAN.package.rTensor |
| 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: | |
| CRAN checks: | rTensor results |
Documentation:
Downloads:
Reverse dependencies:
| Reverse imports: | ccTensor, dcTensor, DelayedTensor, fase, gcTensor, iTensor, LTAR, mwTensor, nnTensor, parafac4microbiome, rMultiNet, rTensor2, RTFA, scITD, scTensor, SmoothTensor, TDbasedUFE, TDbasedUFEadv, TensorClustering, tensorMiss, TensorPreAve, tensorTS, Tlasso, TransGraph, TransTGGM, TRES, WormTensor |
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| Reverse suggests: | oddnet |
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