Statistical approach to inverse distance interpolation

Original Paper

Abstract

Inverse distance interpolation is a robust and widely used estimation technique. Variants of kriging are often proposed as statistical techniques with superior mathematical properties such as minimum error variance; however, the robustness and simplicity of inverse distance interpolation motivate its continued use. This paper presents an approach to integrate statistical controls such as minimum error variance into inverse distance interpolation. The optimal exponent and number of data may be calculated globally or locally. Measures of uncertainty and local smoothness may be derived from inverse distance estimates.

Keywords

Estimation variance Kriging Local estimation Optimal parameters 

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Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  1. 1.Centre for Computational Geostatistics, Department of Civil and Environmental EngineeringUniversity of AlbertaEdmontonCanada

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