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rTensor  

Tools for Tensor Analysis and Decomposition
View on CRAN: Click here


Download and install rTensor package within the R console
Install from CRAN:
install.packages("rTensor")

Install from Github:
library("remotes")
install_github("cran/rTensor")

Install by package version:
library("remotes")
install_version("rTensor", "1.4.9")



Attach the package and use:
library("rTensor")
Maintained by
Koki Tsuyuzaki
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2014-01-28
Latest Update: 2021-05-15
Description:
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.
How to cite:
Koki Tsuyuzaki (2014). rTensor: Tools for Tensor Analysis and Decomposition. R package version 1.4.9, https://cran.r-project.org/web/packages/rTensor. Accessed 05 Mar. 2026.
Previous versions and publish date:
1.0 (2014-01-28 00:32), 1.1 (2014-04-08 15:23), 1.2 (2014-11-11 07:59), 1.3 (2015-12-15 00:56), 1.4.1 (2020-03-22 10:32), 1.4.8 (2021-05-15 08:20), 1.4 (2018-12-04 11:20)
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Complete documentation for rTensor
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