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HiDimDA (version 0.1-1)

High Dimensional Discriminant Analysis

Description

Performs Linear Discriminant Analysis in High Dimensional problems based on covariance estimators derived from low dimensional factor models. Includes routines for classifier training, prediction, cross-validation and variable selection.

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Version

Install

install.packages('HiDimDA')

Monthly Downloads

193

Version

0.1-1

License

GPL (>= 3)

Maintainer

Antonio Duarte Silva

Last Published

June 15th, 2011

Functions in HiDimDA (0.1-1)

solveFq

Solve methods for SigFq and SigFqInv objects
SinghDS

Singh Prostate Cancer Data Set
RFlda

High-Dimensional Factor-based Linear Discriminant Analysis.
HiDimDA-package

High Dimensional Discriminant Analysis
predict.RFlda

Classify Multivariate Observations by Linear Discrimination based on Factor models.
DACrossVal

Cross Validation for Discriminant Analysis Classification Rules
SigFq

SigFq objects: covariance matrices associated with a q-factor model
AlonDS

Alon Colon Cancer Data Set
SigFqInv

SigFqInv objects: precision (inverse of covariance) matrices associated with a q-factor model
FrobSigAp

Approximation of Covariance Matrices from q-factor models
SelectV

Variable Selection for High-Dimensional Discriminant Analysis.
MatMultSigFq

MatMultSigFq: Specialized matrix multiplication of SigFq and SigFqInv objects
HiDimDA-internal

Internal HiDimDA Functions