GDS1615                 GDS1615 data introduced in Burczynski et al.
                        (2012).
ROAD                    Solution path for regularized optimal affine
                        discriminant
SOS                     Solution path for sparse discriminant analysis
SeSDA                   Solution path for semiparametric sparse
                        discriminant analysis
adjten                  Adjust tensor for covariates.
adjvec                  Adjust vector for covariates.
catch                   Fit a CATCH model and predict categorical
                        response.
catch_matrix            Fit a CATCH model for matrix and predict
                        categorical response.
csa                     Colorimetric sensor array (CSA) data
cv.SeSDA                Cross validation for semiparametric sparse
                        discriminant analysis
cv.catch                Cross-validation for CATCH
cv.dsda                 Cross validation for direct sparse discriminant
                        analysis
cv.msda                 Cross-validation for DSDA/MSDA through function
                        'msda'
dsda                    Solution path for direct sparse discriminant
                        analysis
dsda.all                Direct sparse discriminant analysis
getnorm                 Direct sparse discriminant analysis
msda                    Fits a regularization path of Sparse
                        Discriminant Analysis and predicts
predict.SeSDA           Prediction for semiparametric sparse
                        discriminant analysis
predict.catch           Predict categorical responses for matrix/tensor
                        data.
predict.dsda            Prediction for direct sparse discriminant
                        analysis
predict.msda            Predict categorical responses for vector data.
sim.bi.vector           Simulate data
sim.tensor.cov          Simulate data
