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.
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| Reverse imports: | ccTensor,CMTFtoolbox,dcTensor,DelayedTensor,fase,gcTensor,iTensor,mwTensor,nnTensor,NPLStoolbox,parafac4microbiome,rMultiNet,RTFA,scITD,scTensor,SmoothTensor,TDbasedUFE,TDbasedUFEadv,TensorClustering,tensorMiss,TensorPreAve,tensorTS,TRES,ttTensor,WormTensor |
| Reverse suggests: | oddnet |
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