comment="Copyright holder of included robinmap library")

comment="Copyright holder of 'Matrix' package from which some code was taken")

Title: Penalized Matrix-Normal Linear Discriminant Analysis
Author: Aaron J. Molstad <molst029@umn.edu>
Maintainer: Aaron J. Molstad <molst029@umn.edu>
Description: Fits the penalized matrix-normal model to be used for linear discriminant analysis with matrix-valued predictors.
Packaged: 2016-10-28 18:20:19 UTC; aaronmolstad

Authors@R: person("Aaron J.", "Molstad", email = "amolstad@fredhutch.org",
Maintainer: Aaron J. Molstad <amolstad@fredhutch.org>
Description: Fits the penalized matrix-normal model to be used for linear discriminant analysis with matrix-valued predictors. For a description of the method, see Molstad and Rothman (2018) <doi:10.1080/10618600.2018.1476249>.
Packaged: 2018-08-02 21:45:36 UTC; aaronmolstad

Title: Model-Based Clustering via Matrix-Variate Mixture Models
Description: Implements finite mixtures of matrix-variate contaminated normal distributions via expectation conditional-maximization algorithm for model-based clustering, as described in Tomarchio et al.(2020) <arXiv:2005.03861>. One key advantage of this model is the ability to automatically detect potential outlying matrices by computing their a posteriori probability of being typical or atypical points. Finite mixtures of matrix-variate t and matrix-variate normal distributions are also implemented by using expectation-maximization algorithms.
Packaged: 2021-06-10 07:39:02 UTC; michael_gallaugher
Maintainer: Michael P.B. Gallaugher <michael_gallaugher@baylor.edu>

Title: Modelling with Sparse And Dense Matrices
Description: Modelling with sparse and dense 'Matrix' matrices, using
modular prediction and response module classes.
Depends: R (>= 2.10.1), stats, utils, methods, Matrix (>= 0.999375-43)

Depends: R (>= 2.10.1), stats, utils, methods, Matrix (>= 0.999375-44)

Depends: R (>= 2.14.0), stats, utils, methods, Matrix (>= 1.0-1)

Imports: stats, methods, Matrix (>= 1.0-1)