Fluctuation free matrix representation based random data partitioning through HDMR

Abstract

High Dimensional Model Representation (HDMR) method does not have the random data partitioning capability because of its nature. This paper focuses on how we can bring the random data partitioning feature to the HDMR method by virtue of the fluctuation free approximation method for the multivariate interpolation problems. The main aim of this work is to construct the universal fluctuation free matrix and to determine the best eigenvalues and the corresponding eigenvectors needed in our new method for partitioning the given multivariate random data through the HDMR method.