General Monotone Model (gemmR)
An R-language implementation of the General Monotone Model proposed by Michael Dougherty and Rick Thomas. It is a procedure for estimating weights for a set of independent predictors that minimize the rank-order inversions between the model predictions and some outcome.

Record Linkage in R (RecordLinkage)
Provides functions for linking and de-duplicating data sets. Methods based on a stochastic approach are implemented as well as classification algorithms from the machine learning domain.

Invariant Causal Prediction (InvariantCausalPrediction)
Confidence intervals for causal prediction in a regression setting. An experimental version is also available for classification.

Easy Management of File Names (filenamer)
Create descriptive file names with ease. New file names are automatically (but optionally) time stamped and placed in date stamped directories. Streamline your analysis pipeline with input and output file names that have informative tags and proper file extensions.

Prediction of Therapeutic Success (EffectTreat)
In personalized medicine, one wants to know, for a given patient and his or her outcome for a predictor (pre-treatment variable), how likely it is that a treatment will be more beneficial than an alternative treatment. This package allows for the quantification of the predictive causal association(i.e., the association between the predictor variable and the individual causal effect of the treatment) and related metrics.

Clustering Indices (clusterCrit)
Compute clustering validation indices