Distribution theory and transform analysis: an introduction to generalized functions, with applications
Introductory steps for an indexing based HDMR algorithm: lumping HDMR
MAASE'08 Proceedings of the 1st WSEAS International Conference on Multivariate Analysis and its Application in Science and Engineering
A new approach for data partitioning through high dimensional model representation
International Journal of Computer Mathematics
An approximation method to model multivariate interpolation problems: Indexing HDMR
Mathematical and Computer Modelling: An International Journal
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An orthogonal hyperprismatic grid whose all nodes are accompanied by the given function values can not be generally constructed due to the random nature of the given function data. This prevents the reduction of the single multivariate interpolation to more than one univariate or bivariate interpolations even approximately. It is generally quite difficult to determine an analytical structure for the target function in these problems. Lumping HDMR method is an indexing based High Dimensional Model Representation (HDMR) algorithm used to reconstruct these types of multivariate data by imposing an indexing scheme to obtain an orthogonal geometry for the given problem. By this way, the training of the given data can be accomplished. The next problem is to determine a reverse algorithm for the testing data. This work is about a new algorithm to find the correct coordinate of the given testing data in the orthogonal geometry obtained through Lumping HDMR.