Better prediction by use of co-data: Adaptive group-regularized ridge regression


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Documentation for package ‘GRridge’ version 1.2.0

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GRridge-package Implements adaptive group-regularized (logistic) ridge regression by use of co-data.
annotationWurdinger R-objects related to the mRNAseq data
auc Area under the ROC curve
coDataWurdinger R-objects related to the mRNAseq data
CpGann Contains 5 R-objects, including the data and the binary response
CpGannFarkas Contains three R-objects, including the data and the binary response
CreatePartition Creates a partition (groups) of variables
dataFarkas Contains three R-objects, including the data and the binary response
dataVerlaat Contains 5 R-objects, including the data and the binary response
dataWurdinger R-objects related to the mRNAseq data
datcenFarkas Contains three R-objects, including the data and the binary response
datcenVerlaat Contains 5 R-objects, including the data and the binary response
datWurdinger_BC R-objects related to the mRNAseq data
diffmeanFarkas Contains 5 R-objects, including the data and the binary response
GRridge Implements adaptive group-regularized (logistic) ridge regression by use of co-data.
grridge Group-regularized (logistic) ridge regression
grridgeCV Returns the cross-validated predictions
hello Hello, World!
matchGeneSets Creates a grouping of variables (genes) from gene sets
mergeGroups Merge groups in a partition
PartitionsSelection Co-data selection in a Group-regularized ridge regression model
predict Predictions for new samples
predict.grridge Predictions for new samples
pvalFarkas Contains 5 R-objects, including the data and the binary response
respFarkas Contains three R-objects, including the data and the binary response
respVerlaat Contains 5 R-objects, including the data and the binary response
respWurdinger R-objects related to the mRNAseq data
roc Produces ROC curve for probabilistic classifiers (e.g. logistic regression)