sda v1.3.7


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Shrinkage Discriminant Analysis and CAT Score Variable Selection

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.

Functions in sda

Name Description
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
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Last month downloads


Date 2015-07-08
License GPL (>= 3)
Packaged 2015-07-08 13:33:12 UTC; strimmer
NeedsCompilation no
Repository CRAN
Date/Publication 2015-07-08 16:28:41

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