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HiDimDA (version 0.2-0)

High Dimensional Discriminant Analysis

Description

Performs Linear Discriminant Analysis in High Dimensional problems based on reliable covariance estimators for problems with(many) more variables than observations. Includes routines for classifier training, prediction, cross-validation and variable selection.

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Version

Install

install.packages('HiDimDA')

Monthly Downloads

193

Version

0.2-0

License

GPL (>= 3)

Maintainer

Antonio Duarte Silva

Last Published

June 29th, 2012

Functions in HiDimDA (0.2-0)

FrobSigAp

Approximation of Covariance Matrices from q-factor models
ShrnkSigE

Shrunken Covariance Estimate.
MatMult

MatMult: Specialized matrix multiplication of DMat, ShrnkMat, ShrnkMatInv, SigFq and SigFqInv objects.
SigFqInv

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

Alon Colon Cancer Data Set
HiDimDA-package

High Dimensional Discriminant Analysis
ShrnkMatInv

ShrnkMatInv objects: precision (inverse of covariance) matrices associated with shrunken estimates of a covariance
MldaInvE

Maximum uncertainty Linear Discriminant Analysis inverse matrix estimator.
RFlda

High-Dimensional Factor-based Linear Discriminant Analysis.
SelectV

Variable Selection for High-Dimensional Discriminant Analysis.
canldaRes

Class object used for storing the results of a canonical high-dimensional linear discriminant analysis.
ShrnkMat

ShrnkMat objects: shrunken matrix estimates of a covariance
Dlda

Diagonal Linear Discriminant Analysis.
SigFq

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

DMat objects: diagonal matrices
HiDimDA-internal

Internal HiDimDA Functions
clldaRes

Class object used for storing the results of a high-dimensional linear discriminant analysis routine (with ldafun argument set to classification).
DACrossVal

Cross Validation for Discriminant Analysis Classification Algorithms
Slda

Shrunken Linear Discriminant Analysis.
Mlda

Maximum uncertainty Linear Discriminant Analysis.
solve

Solve methods for DMat, ShrnkMat, ShrnkMatInv, SigFq and SigFqInv objects.
CovE

Generic methods for extracting covariance and inverse covariance matrices from objects storing the results of a Linear Discriminant Analysis