A new class of binning free, multivariate goodness-of-fit tests: the energy tests

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dc.creatorAslan, B.
dc.creatorZech, G.
dc.date2002-03-07
dc.date2003-04-29
dc.date.accessioned2026-07-07T03:35:01Z
dc.date.available2026-07-07T03:35:01Z
dc.descriptionWe present a new class of multivariate binning-free and nonparametric goodness-of-fit tests. The test quantity \emph{energy} is a function of the distances of observed and simulated observations in the variate space. The simulation follows the probability distribution function $f_{0}$ of the null hypothesis. The distances are weighted with a weighting function which can be adjusted to the variations of $f_{0}$. We have investigated the power of the test for a uniform and a Gaussian distribution of one or two variates, respectively and compared it to that of conventional tests. The energy test with a Gaussian weighting function is closely related to the Pearson $χ^{2}$ test but is more powerful in most applications and avoids arbitrary bin boundaries. The test is especially powerful in the multivariate case.
dc.description17 pages,8 figures, corrected version
dc.identifierhttps://arxiv.org/abs/hep-ex/0203010
dc.identifierhttp://arxiv.org/abs/hep-ex/0203010
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/37205
dc.subjectHigh Energy Physics - Experiment
dc.subjectData Analysis, Statistics and Probability
dc.titleA new class of binning free, multivariate goodness-of-fit tests: the energy tests
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