RELsharpening           Ridge/Enet/LASSO Sharpening via the mean/local
                        polynomial regression with large
                        bandwidth/linear regression.
data_sharpening         Penalized data sharpening for Local Linear,
                        Quadratic and Cubic Regression
dpilc                   Select a Bandwidth for Local Quadratic and
                        Cubic Regression
getA                    Local Polynomial Estimator Matrix Construction
getB                    Shape Constraint Matrix Construction
noontemp                Noon Temperatures in Winnipeg, Manitoba
numericalDerivative     Numerical Derivative of Smooth Function
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.
relsharpen              Ridge/Enet/LASSO Sharpening via the penalty
                        matrix.
testfun                 Functions for Testing Purposes
