# Ridge Group Sparse Optimization Problem for Estimation of a Meta Model Based on Reproducing Kernel Hilbert Spaces

## Documentation for package ‘RKHSMetaMod’ version 1.1

- DESCRIPTION file.

## Help Pages

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.
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.
PredErr | Function to calculate the prediction error.
RKHSgrplasso | Function to fit a solution of an RKHS Group Lasso problem.
RKHSMetaMod | 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.
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.
SI_emp | Function to calculate the empirical sensitivity indices for an input or a group of inputs.