rTensor (1.2)

Tools for tensor analysis and decomposition.


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 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, product, and SVD, as defined in Kilmer et al. (2013). Some auxiliary functions include the Khatri-Rao 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.

Maintainer: James Li
Author(s): James Li and Jacob Bien and Martin Wells

License: GPL (>= 2)

Uses: Does not use any package
Reverse depends: nnTensor, tensorregress, TRES

Released over 5 years ago.