Paper Info
Title
An approximation method to model multivariate interpolation problems: Indexing HDMR
Abstract
Dealing with univariate or bivariate data sets instead of a multivariate data set is an important concern in interpolation problems and computer-based applications. This paper presents a new data partitioning method that partitions the given multivariate data set into univariate and bivariate data sets and constructs an approximate analytical structure that interpolates function values at arbitrarily distributed points of the given grid. A number of numerical implementations are also given to show the performance of this new method.
Year
DOI
Venue
2011
10.1016/j.mcm.2011.01.027
Mathematical and Computer Modelling
Keywords
Field
DocType
data partitioning,computer-based application,multivariate interpolation problem,multivariate data set,new data,multivariate data,important concern,high-dimensional model representation,bivariate data,interpolates function value,multivariate analysis,bivariate data set,combinatorial analysis,new method,approximation,indexing hdmr,approximation method,approximate analytical structure,indexation,multivariate interpolation
Nearest-neighbor interpolation,Bivariate data,Mathematical optimization,Multivariate interpolation,Multivariate statistics,Interpolation,Algorithm,Statistics,High-dimensional model representation,Univariate,Numerical analysis,Mathematics
Journal
Volume
Issue
ISSN
53
9-10
Mathematical and Computer Modelling
Citations 
PageRank 
References 
6
0.49
7
Authors
1
Name
Order
Citations
PageRank
M. Alper Tunga1405.44