| bandwidth | Bandwidth selectors |
| bw_canonical_factor | Bandwidth selectors |
| bw_comparator_cv | Bandwidth selectors |
| bw_convert | Bandwidth selectors |
| bw_flattop | Bandwidth selectors |
| bw_nrd_robust | Bandwidth selectors |
| comparator_density | Infinite-order kernel density estimators |
| ise | Integrated squared error against a known density |
| kernels | Kernels for the perturbed estimator |
| plot.tiltdens_md | Contour plot of a bivariate fit |
| predict.tiltdens | Evaluate a fitted density at new points |
| predict.tiltdens_md | Evaluate a fitted density at new points |
| print.summary.tiltdens | Summarise a tilted or sharpened density fit |
| print.tiltdens | Print a tilted or sharpened density fit |
| print.tiltdens_md | Print a multivariate fit |
| real_ga | Real-coded genetic algorithm for small box-constrained problems |
| sharpen_density | Data-sharpened density estimation |
| sinc_density | Infinite-order kernel density estimators |
| summary.tiltdens | Summarise a tilted or sharpened density fit |
| tilt_cv | Cross-validation criterion for a tilted estimator |
| tilt_density | Tilted density estimation by distance to a comparator |
| tilt_density_cv | Tilted density estimation by cross-validation |
| tilt_kernel | Kernels for the perturbed estimator |
| tilt_kernels | Kernels for the perturbed estimator |
| trapezoid_density | Infinite-order kernel density estimators |