Ridge Group Sparse Optimization Problem for Estimation of a Meta Model Based on Reproducing Kernel Hilbert Spaces
Function to fit a solution with q active groups of an RKHS Group Lasso...
Function to calculate the empirical sensitivity indices for an input o...
Function to calculate the Gram matrices and their eigenvalues and eige...
Function to fit a solution of an RKHS Group Lasso problem.
Function to produce a sequence of meta models that are the solutions o...
Function to produce a sequence of meta models, with at most qmax activ...
Function to find the maximal value of the penalty parameter in the RKH...
Function to fit a solution of the RKHS Ridge Group Sparse problem.
Function to calculate the prediction error.
Set of Rcpp and R functions to produce a sequence of meta models that ...
Estimates the Hoeffding decomposition of an unknown function by solving ridge group sparse optimization problem based on reproducing kernel Hilbert spaces, and approximates its sensitivity indices (see Kamari, H., Huet, S. and Taupin, M.-L. (2019) <arXiv:1905.13695>).