| data_sharpening | Penalized data sharpening for Local Linear, Quadratic and Cubic Regression | 
| derivOperator | Shape Constraint Matrix Construction | 
| dpilc | Select a Bandwidth for Local Quadratic and Cubic Regression | 
| dpilc_PTW | dpilc_PTW: Local Polynomial Bandwith Estimation with Blockwise Selection and Pointwise Results | 
| DR_sharpen | Shape-Constrained Local Linear Regression via Douglas-Rachford | 
| lprOperator | Local Polynomial Estimator Matrix Construction | 
| noontemp | Noon Temperatures in Winnipeg, Manitoba | 
| numericalDerivative | Numerical Derivative of Smooth Function | 
| projection_C | Projection operator for rectangle or nonnegative space | 
| projection_nb | Projection operator for norm balls. | 
| relsharpen | Ridge/Enet/LASSO Sharpening via the penalty matrix. | 
| RELsharpening | Ridge/Enet/LASSO Sharpening via the mean/local polynomial regression with large bandwidth/linear regression. | 
| relsharp_bigh | Ridge/Enet/LASSO Sharpening via the local polynomial regression with large bandwidth. | 
| relsharp_bigh_c | Ridge/Enet/LASSO Sharpening via the local polynomial regression with large bandwidth and then applying the residual sharpening method. | 
| relsharp_linear | Ridge/Enet/LASSO Sharpening via the linear regression. | 
| relsharp_linear_c | Ridge/Enet/LASSO Sharpening via the linear regression and then applying the residual sharpening method. | 
| relsharp_mean | Ridge/Enet/LASSO Sharpening via the Mean | 
| relsharp_mean_c | Ridge/Enet/LASSO Sharpening via the Mean and then applying the residual sharpening method. | 
| testfun | Functions for Testing Purposes |