| adaptedData | Convenience function for returning adapted data |
| adaptedData.fairadapt | Convenience function for returning adapted data |
| adaptedData.fairadaptBoot | Convenience function for returning adapted data |
| autoplot.fairadapt | Plotting data before and after adaptation |
| compas | COMPAS dataset |
| computeQuants | Compute quantiles generic for the quantile learning step |
| fairadapt | Fair data adaptation (fairadapt) |
| fairadaptBoot | Fairadapt boostrap wrapper |
| fairTwins | Fair twin inspection convenience function |
| gov_census | Census information of US government employees |
| graphModel | Obtaining the graphical causal model (GCM) |
| linearQuants | Quantile engine constructor for the quantile learning step |
| mcqrnnQuants | Quantile engine constructor for the quantile learning step |
| plot.fairadapt | Plotting data before and after adaptation |
| predict.fairadapt | Prediction function for new data from a saved 'fairadapt' object |
| predict.fairadaptBoot | Prediction function for new data from a saved 'fairadaptBoot' object |
| print.fairadapt | Fair data adaptation (fairadapt) |
| print.fairadaptBoot | Fairadapt boostrap wrapper |
| print.summary.fairadapt | Summarizing fairadapt fit |
| print.summary.fairadaptBoot | Summarizing fairadaptBoot fit |
| quantFit | Quality of quantile fit statistics |
| rangerQuants | Quantile engine constructor for the quantile learning step |
| summary.fairadapt | Summarizing fairadapt fit |
| summary.fairadaptBoot | Summarizing fairadaptBoot fit |
| uni_admission | University admission data of 1,000 students |
| visualizeGraph | Visualize graphical causal model |