Title
Statistical measures of two dimensional point set uniformity
Abstract
Three different classes of statistical measures of uniformity, namely, discrepancy, point-to-point measures and volumetric measures, are described and compared in this paper. Correlation studies are carried out to compare their performance in discerning uniformity of random and quasi-random point sets with respect to human perception of uniformity. Some of the measures reported in the literature are found to be able to characterize and rank very limited class of point sets correctly. A new approach to better characterize uniformity based on the physical analogy of potential energy is proposed. An approximate closed-form expression measuring the average uniformity of point set generated by spatial Poisson process is also derived theoretically. A novel application in signal processing is presented and extensive simulations are carried out to corroborate the validity of the proposed technique.
Year
DOI
Venue
2012
10.1016/j.csda.2011.12.005
Computational Statistics & Data Analysis
Keywords
Field
DocType
discerning uniformity,average uniformity,limited class,human perception,dimensional point set uniformity,statistical measure,proposed technique,extensive simulation,different class,correlation study,approximate closed-form expression,quasi-random point set,k nearest neighbor,poisson process,k,potential energy,signal processing,voronoi tessellation,phase plane,point to point
k-nearest neighbors algorithm,Signal processing,Phase plane,Potential energy,Correlation,Voronoi diagram,Point set,Statistics,Spatial Poisson process,Mathematics
Journal
Volume
Issue
ISSN
56
6
0167-9473
Citations 
PageRank 
References 
1
0.36
15
Authors
3
Name
Order
Citations
PageRank
Meng Sang Ong1101.52
Ye Chow Kuang27219.81
Melanie Po-Leen Ooi37018.35