Le Cam spacings theorem in dimension two

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dc.creatorCucala, Lionel
dc.date2005-07-18
dc.date.accessioned2026-07-07T08:07:03Z
dc.date.available2026-07-07T08:07:03Z
dc.descriptionThe definition of spacings associated to a sequence of random variables is extended to the case of random vectors in [0,1]^2. Beirlant & al. (1991) give an alternative proof of the Le Cam (1958) theorem concerning asymptotic normality of additive functions of uniform spacings in [0,1]. I adapt their technique to the two-dimensional case, leading the way to new directions in the domain of Complete Spatial Randomness (CSR) testing.
dc.identifierhttps://arxiv.org/abs/math/0507367
dc.identifierhttp://arxiv.org/abs/math/0507367
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/130810
dc.subjectStatistics Theory
dc.subjectMSC 2000: 60F05, 62G30
dc.titleLe Cam spacings theorem in dimension two
dc.typetext

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