tensor_decomp: Implements tensor factorization methods, Tucker and...
In KSheu/ksheu.lib: KSheu Library1

Tucker: If there is no truncationin one of the modes, then this is the same as the MPCA,mpca. If there is no truncation in all the modes, then this is the same as the HOSVD,hosvd.

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tensor_decomp(matrix, dims, method, xlabs = rownames(matrix),
  ylabs = colnames(matrix)[-1], zlabs = NULL, ranks = A@modes,
  savename = "TEST", plot = F)

`matrix`	matrix that gets coverted to multidimensional array that get converted through as.tensor(arr)
`dims`	dimensions to fold the input matrix
`method`	"tucker" or "cp"
`plot`	plot heamtmaps of eigenvectors
`z_labs`	labels for the extra dimensions created, rows and colnames are the x and y axis labs
`rank`	default = 3, number (if CP) or vector of numbers (if tucker) that is <= the ranks of the tensor