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sda (version 1.3.7)

Shrinkage Discriminant Analysis and CAT Score Variable Selection

Description

Provides an efficient framework for high-dimensional linear and diagonal discriminant analysis with variable selection. The classifier is trained using James-Stein-type shrinkage estimators and predictor variables are ranked using correlation-adjusted t-scores (CAT scores). Variable selection error is controlled using false non-discovery rates or higher criticism.

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Version

Install

install.packages('sda')

Monthly Downloads

1,855

Version

1.3.7

License

GPL (>= 3)

Maintainer

Korbinian Strimmer

Last Published

July 8th, 2015

Functions in sda (1.3.7)

predict.sda

Shrinkage Discriminant Analysis 3: Prediction Step
khan2001

Childhood Cancer Study of Khan et al. (2001)
sda-package

The sda Package
catscore

Estimate CAT Scores and t-Scores
sda-internal

Internal sda functions
singh2002

Prostate Cancer Study of Singh et al. (2002)
centroids

Group Centroids and (Pooled) Variances
sda

Shrinkage Discriminant Analysis 2: Training Step
sda.ranking

Shrinkage Discriminant Analysis 1: Predictor Ranking