Description of R package MGSDA

MGSDA (Multi-Group Sparse Discriminant Analysis) is an R package that implements methods described in

• I.Gaynanova, J.Booth and M. Wells “Simultaneous sparse estimation of canonical vectors in the p>>n setting.”, JASA, 111(514), 696-706.

The package is available from CRAN.

To install from Github:

devtools::install_github("irinagain/MGSDApackage")

The main functions are cv.dLDA(cross-validation), dLDA(fitting for specified value of tuning parameter) and classifyV(classification). Each function has a documentation with a simple example which can be accessed using standard ? commands in R (i.e. ?cv.dLDA).

Please feel free to contact me at irinag [at] stat [dot] tamu [dot] edu if you have any questions or experience problems with the package.

Simple example

library(MGSDA)

### Example 1
# generate training data
n <- 10
p <- 100
G <- 3
ytrain <- rep(1:G, each = n)
set.seed(1)
xtrain <- matrix(rnorm(p * n * G), n * G, p)

# find matrix of canonical vectors V
V <- dLDA(xtrain, ytrain, lambda = 0.1)
sum(rowSums(V) != 0)

# generate test data
m <- 20
set.seed(3)
xtest <- matrix(rnorm(p * m), m, p)

# perform classification
ytest <- classifyV(xtrain, ytrain, xtest, V)