AA                      Helper functions for calculating gradient of
                        least-squares Shuffled Isotonic Regression
                        criterion, for Laplace or for Gaussian errors
UMR                     UMR: For computing an estimator in Unlinked
                        Monotone Regression.
UMR_curv_generic        @title Second derivative computations of
                        least-squares Unlinked Isotonic Regression
                        criterion ("SIR" comes from "shuffled isotonic
                        regression" although this terminology is now
                        outdated).
UMRactiveSet            An active set approach to minimizing objective
                        in Unlinked Monotone Regression
UMRactiveSet_trust      An active set approach to minimizing objective
                        in Unlinked Monotone Regression
UMRactiveSet_trust2     An active set approach to minimizing objective
                        in Unlinked Monotone Regression
UMRgradDesc             Basic gradient descent implementation
UMRgradDesc_PC          Gradient Descent implemented for Piecewise
                        Constant functions
UMRgradDesc_fixed_df    Gradient Descent with a fixed number of
                        constant pieces (degrees of freedom)
UMRgrad_generic         Gradient of least-squares Shuffled Isotonic
                        Regression criterion
UMRhess                 Compute Hessian of Unlinked Monotone Regression
                        objective function from Balabdaoui, Doss, and
                        Durot
gradDesc_fixed_df       Gradient Descent with a fixed number of
                        constant pieces (degrees of freedom)
objective_fn_numint     Compute Unlinked Monotone Regression objective
                        function numerically
umr_deconv              Carpentier and Schluter 2016 deconvolution
                        method for unmatched monotone regression
