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 | |
| No Results! | ||
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Details
| Date | 2015-07-08 |
| License | GPL (>= 3) |
| URL | http://strimmerlab.org/software/sda/ |
| Packaged | 2015-07-08 13:33:12 UTC; strimmer |
| NeedsCompilation | no |
| Repository | CRAN |
| Date/Publication | 2015-07-08 16:28:41 |
| depends | base (>= 3.0.2) , corpcor (>= 1.6.8) , entropy (>= 1.2.1) , fdrtool (>= 1.2.15) , R (>= 3.0.2) |
| suggests | crossval (>= 1.0.3) |
| imports | graphics , stats , utils |
| Contributors | Korbinian Strimmer, Sebastian Gibb, Verena Zuber, Miika Ahdesmaki |
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