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DC Field | Value | Language |
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dc.contributor.author | Lopes, RHC | - |
dc.contributor.author | Hobson, PR | - |
dc.contributor.author | Reid, ID | - |
dc.coverage.spatial | 9 | en |
dc.date.accessioned | 2008-08-04T15:13:51Z | - |
dc.date.available | 2008-08-04T15:13:51Z | - |
dc.date.issued | 2008 | - |
dc.identifier.citation | Journal of Physics: Conference Series. 120(2008) 042019, Jun 2008 | en |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/2571 | - |
dc.description.abstract | Goodness-of-fit statistics measure the compatibility of random samples against some theoretical or reference probability distribution function. The classical one-dimensional Kolmogorov-Smirnov test is a non-parametric statistic for comparing two empirical distributions which defines the largest absolute difference between the two cumulative distribution functions as a measure of disagreement. Adapting this test to more than one dimension is a challenge because there are 2^d-1 independent ways of ordering a cumulative distribution function in d dimensions. We discuss Peacock's version of the Kolmogorov-Smirnov test for two-dimensional data sets which computes the differences between cumulative distribution functions in 4n^2 quadrants. We also examine Fasano and Franceschini's variation of Peacock's test, Cooke's algorithm for Peacock's test, and ROOT's version of the two-dimensional Kolmogorov-Smirnov test. We establish a lower-bound limit on the work for computing Peacock's test of Omega(n^2.lg(n)), introducing optimal algorithms for both this and Fasano and Franceschini's test, and show that Cooke's algorithm is not a faithful implementation of Peacock's test. We also discuss and evaluate parallel algorithms for Peacock's test. | en |
dc.format.extent | 2276534 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | en | - |
dc.publisher | IOP | en |
dc.rights | Copyright © Institute of Physics and IOP Publishing Limited 2008 | en |
dc.subject | Statistical tests | en |
dc.subject | Kolmogorov-Smirnov | en |
dc.subject | Algorithms | en |
dc.subject | Computer science | en |
dc.title | Computationally efficient algorithms for the two-dimensional Kolmogorov-Smirnov test | en |
dc.type | Research Paper | en |
dc.identifier.doi | http://dx.doi.org/10.1088/1742-6596/120/4/042019 | - |
Appears in Collections: | Electronic and Electrical Engineering Dept of Electronic and Electrical Engineering Research Papers |
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File | Description | Size | Format | |
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CHEP07-jpconf8_119_042019.pdf | 2.22 MB | Adobe PDF | View/Open |
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