Comparison of data by Pearson product-moment correlation
coefficients is prone to outliers. The problem can be
alleviated by normalizing data with outliers before computing
the Pearson correlation coefficient. The sample provides such
normalization by optimal power space transformation.

Optimal Combinations of Diagnostic Tests Based on AUC
Searches for optimal linear combination of multiple
diagnostic tests (markers) that maximizes the area under the
receiver operating characteristic curve (AUC); performs an
approximated cross-validation for estimating the AUC associated
with the estimated coefficients.

Estimation of optimal number of biomarkers for two-group
microarray based classifications at a given error tolerance
level for various classification rules
Estimates optimal number of biomarkers for two-group
classification based on microarray data

MASS, randomForest, e1071,ipred, msm, Matrix

Estimation of Optimal Number of Biomarkers for Two-Group
Microarray Based Classifications at a Given Error Tolerance
Level for Various Classification Rules
MASS, randomForest, e1071,ipred, msm, rgl, Matrix
Estimates optimal number of biomarkers for two-group
classification based on microarray data.

Determine Optimal Clustering Algorithm and Number of Clusters
Michael Sekula <michael.sekula@louisville.edu>,
Somnath Datta <somnath.datta@louisville.edu>,
and Susmita Datta <susmita.datta@louisville.edu>
Cluster analysis using statistical and biological
validation measures for both transformed and count data.
clValid, RankAggreg, mclust, methods, cluster, gplots,
kohonen, MBCluster.Seq

Cluster analysis using statistical and biological
validation measures for both continuous and count data.
grDevices, graphics, stats, utils, clValid, RankAggreg,
mclust, methods, cluster, gplots, kohonen, MBCluster.Seq

grDevices, graphics, stats, utils, RankAggreg, mclust,
methods, cluster, gplots, kohonen, MBCluster.Seq,
orphaned-Code.R optCluster-Classes.R optCluster-Methods.R
optCluster-Internal.R optCluster-Functions.R