rTensor is 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 also 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 elementwise operations. rTensor also implements various tensor decomposition, including CP, GLRAM, MPCA, PVD, and Tucker. For tensors with 3 modes, rTensor also implements transpose, product, and SVD, as defined in Kilmer et al. (2013). Some auxiliary functions include the KhatriRao product, Kronecker product, and the Hamadard product for a list of matrices. Development of rTensor has been generously supported by Cornell's Department of Statistical Science.
Package details 


Author  James Li and Jacob Bien and Martin Wells 
Maintainer  James Li <[email protected]> 
License  GPL (>= 2) 
Version  1.3 
URL  http://jamesyili.github.io/rTensor 
Package repository  View on GitHub 
Installation 
Install the latest version of this package by entering the following in R:

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