Package: rTensor
Type: Package
Title: Tools for tensor analysis and decomposition
Version: 1.1
Author: James Li and Jacob Bien and Martin Wells
Maintainer: James Li <jamesyili@gmail.com>
Description: 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.
License: GPL (>= 2)
Date: 2014-01-27
URL: http://jamesyili.github.io/rTensor
Depends: methods
Collate: 'rTensor_Class.R' 'rTensor_Decomp.R' 'rTensor_Misc.R'
Packaged: 2014-04-08 13:09:37 UTC; jamesyili
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2014-04-08 15:23:07

Package: rTensor
Type: Package
Title: Tools for tensor analysis and decomposition
Version: 1.2
Author: James Li and Jacob Bien and Martin Wells
Maintainer: James Li <jamesyili@gmail.com>
Description: 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.
License: GPL (>= 2)
Depends: methods
Date: 2014-11-05
URL: http://jamesyili.github.io/rTensor
Packaged: 2014-11-11 00:47:37 UTC; jamesyili
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2014-11-11 07:59:50