Fast algorithms for a space-time concordance measure

Sergio Rey ()

Computational Statistics, 2014, vol. 29, issue 3, 799-811

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 $$\tau $$ τ the original implementation of the concordance measure relied on a brute force $$O(n^2)$$ 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 $$O(n log(n) +np)$$ O ( n l o g ( n ) + n p ) where $$p$$ 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. Copyright Springer-Verlag Berlin Heidelberg 2014

Keywords: Spatial concordance; Autocorrelation; Rank correlation (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s00180-013-0461-2

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