Computational Statistics

, Volume 29, Issue 3, pp 799–811

Fast algorithms for a space-time concordance measure

Original Paper

DOI: 10.1007/s00180-013-0461-2

Cite this article as:
Rey, S.J. Comput Stat (2014) 29: 799. doi:10.1007/s00180-013-0461-2

Abstract

This paper presents a number of algorithms for a recently developed measure of space-time concordance. Based on a spatially explicit version of Kendall’s \(\tau \) the original implementation of the concordance measure relied on a brute force \(O(n^2)\) algorithm which has limited its use to modest sized problems. Several new algorithms have been devised which move this run time to \(O(n log(n) +np)\) where \(p\) is the expected number of spatial neighbors for each unit. Comparative timing of these alternative implementations reveals dramatic efficiency gains in moving away from the brute force algorithms. A tree-based implementation of the spatial concordance is also found to dominate a merge sort implementation.

Keywords

Spatial concordanceAutocorrelationRank correlation

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Arizona State UniversityTempeUSA