fnorm-methods

fnorm

fnorm,Tensor-method

Returns the Frobenius norm of the Tensor instance.

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.

Koki Tsuyuzaki

rTensor

Tools for Tensor Analysis and Decomposition

James Li

Jacob Bien

Martin Wells

fnorm-methods function

<dl><dt>tnsr</dt>
<dd>the Tensor instance</dd></dl>

Arguments

Tensor Frobenius Norm — fnorm-methods

<dl>

<dt>tnsr</dt>
<dd>the Tensor instance</dd>

</dl>

fnorm-methods: Tensor Frobenius Norm

Description

Usage

Value

Arguments

Details

Examples