SQDA: Sparse Quadratic Discriminant Analysis

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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.

Author
Jiehuan Sun
Date of publication
2014-10-01 07:22:24
Maintainer
Jiehuan Sun <jiehuan.sun@yale.edu>
License
GPL-3
Version
1.0

View on CRAN

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

Files in this package

SQDA
SQDA/NAMESPACE
SQDA/data
SQDA/data/exampledata.rda
SQDA/data/datalist
SQDA/R
SQDA/R/SQDA.R
SQDA/MD5
SQDA/DESCRIPTION
SQDA/man
SQDA/man/train.data.Rd
SQDA/man/sortgene.Rd
SQDA/man/test.data.Rd
SQDA/man/cross.Rd
SQDA/man/sGdaCV2.Rd
SQDA/man/simpleAGG3.Rd
SQDA/man/sQDA.Rd
SQDA/man/SQDA-package.Rd
SQDA/man/exampledata.Rd
SQDA/man/sGda.Rd