Multivariate data modelling by metric approximants

Authors:
M. Brannigan
Affiliations:
Department of Statistics and Computer Science, University of Georgia, Athens. GA30602, USA
Venue:
Computational Statistics & Data Analysis
Year:
1985

Citing 2
Cited 0

Computer Aided Geometric Design; Proceedings of a Conference Held at the University of Utah, Salt Lake City, Utah, March 18-21, 1974

Computer Aided Geometric Design; Proceedings of a Conference Held at the University of Utah, Salt Lake City, Utah, March 18-21, 1974
A two-dimensional interpolation function for irregularly-spaced data

ACM '68 Proceedings of the 1968 23rd ACM national conference

Quantified Score

Hi-index	0.03

Visualization

Abstract

Shepard developed a method for the interpolation of arbitrarily spaced discrete data points of two variables. We extend this scheme to approximate, by a smooth function, discrete sets of multivariate data points. No regularity is assumed for the data distribution, and we allow the dependent variable to contain error. The method presented here can be applied to the statistical analysis of experimental data as well as to the compression of data in computer graphics and computer aided design.