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HiDimDA (version 0.2-4)

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

240

Version

0.2-4

License

GPL (>= 3)

Maintainer

Antonio Duarte Silva

Last Published

October 19th, 2015

Functions in HiDimDA (0.2-4)

clldaRes

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

DMat objects: diagonal matrices
Dlda

Diagonal Linear Discriminant Analysis.
FrobSigAp

Approximation of Covariance Matrices from q-factor models
MatMult

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

Alon Colon Cancer Data Set
HiDimDA-internal

Internal HiDimDA Functions
CovE

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

Maximum uncertainty Linear Discriminant Analysis.
canldaRes

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

High-Dimensional Factor-based Linear Discriminant Analysis.
SigFq

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

Maximum uncertainty Linear Discriminant Analysis inverse matrix estimator.
SelectV

Variable Selection for High-Dimensional Supervised Classification.
SigFqInv

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

ShrnkMat objects: shrunken matrix estimates of a covariance
ShrnkMatInv

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

Shrunken Covariance Estimate.
Slda

Shrunken Linear Discriminant Analysis.
solve

Solve methods for ‘DMat’, ‘ShrnkMat’, ‘ShrnkMatInv’, ‘SigFq’ and ‘SigFqInv’ objects.
DACrossVal

Cross Validation for Discriminant Analysis Classification Algorithms
HiDimDA-package

High Dimensional Discriminant Analysis