SQDA: Sparse Quadratic Discriminant Analysis
Version 1.0

Sparse Quadratic Discriminant Analysis (SQDA) can be performed. In SQDA, the covariance matrix are assumed to be block-diagonal.And, for each block, sparsity assumption is imposed on the covariance matrix. It is useful in high-dimensional setting.

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AuthorJiehuan Sun
Date of publication2014-10-01 07:22:24
MaintainerJiehuan Sun <jiehuan.sun@yale.edu>
LicenseGPL-3
Version1.0
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("SQDA")

Man pages

cross: generate cross-validation ids
exampledata: exampeldata
sGda: Prediction function
sGdaCV2: Cross-validation function
simpleAGG3: Blockwise classifiers
sortgene: Gene sorter
sQDA: Spase Quadratic Discriminant Analysis
SQDA-package: Sparse Quadratic Discriminant Analysis
test.data: testing data
train.data: training data

Functions

SQDA Man page
SQDA-package Man page
cross Man page Source code
exampledata Man page
sGda Man page Source code
sGdaCV2 Man page Source code
sQDA Man page Source code
simpleAGG3 Man page Source code
sortgene Man page Source code
test.data Man page
train.data Man page

Files

NAMESPACE
data
data/exampledata.rda
data/datalist
R
R/SQDA.R
MD5
DESCRIPTION
man
man/train.data.Rd
man/sortgene.Rd
man/test.data.Rd
man/cross.Rd
man/sGdaCV2.Rd
man/simpleAGG3.Rd
man/sQDA.Rd
man/SQDA-package.Rd
man/exampledata.Rd
man/sGda.Rd
SQDA documentation built on May 19, 2017, 7:26 a.m.