PredErr                 Function to calculate the prediction error.
RKHSMetMod              Function to produce a sequence of meta models
                        that are the solutions of the RKHS Ridge Group
                        Sparse or RKHS Group Lasso optimization
                        problems.
RKHSMetMod_qmax         Function to produce a sequence of meta models,
                        with at most qmax active groups in each meta
                        model. The meta models are the solutions of the
                        RKHS Ridge Group Sparse or RKHS Group Lasso
                        optimization problems.
RKHSMetaMod-package     Set of Rcpp and R functions to produce a
                        sequence of meta models that are the solutions
                        of the RKHS Ridge Group Sparse or RKHS Group
                        Lasso optimization problems, calulate their
                        associated prediction errors as well as their
                        empirical sensitivity indices.
RKHSgrplasso            Function to fit a solution of an RKHS Group
                        Lasso problem.
SI_emp                  Function to calculate the empirical sensitivity
                        indices for an input or a group of inputs.
calc_Kv                 Function to calculate the Gram matrices and
                        their eigenvalues and eigenvectors for a chosen
                        reproducing kernel.
grplasso_q              Function to fit a solution with q active groups
                        of an RKHS Group Lasso problem.
mu_max                  Function to find the maximal value of the
                        penalty parameter in the RKHS Group Lasso
                        problem.
pen_MetMod              Function to fit a solution of the RKHS Ridge
                        Group Sparse problem.
