Consistance d'un estimateur de minimum de variance étendue

dc.creatorRynkiewicz, Joseph
dc.date2008-02-21
dc.date.accessioned2026-07-07T09:22:33Z
dc.date.available2026-07-07T09:22:33Z
dc.descriptionWe consider a generalization of the criterion minimized by the K-means algorithm, where a neighborhood structure is used in the calculus of the variance. Such tool is used, for example with Kohonen maps, to measure the quality of the quantification preserving the neighborhood relationships. If we assume that the parameter vector is in a compact Euclidean space and all it components are separated by a minimal distance, we show the strong consistency of the set of parameters almost realizing the minimum of the empirical extended variance.
dc.identifierhttps://arxiv.org/abs/0802.3190
dc.identifierhttp://arxiv.org/abs/0802.3190
dc.identifierComptes Rendus de l Académie des Sciences - Series I - Mathematics 341 (2005) 133-136
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/155415
dc.subjectStatistics Theory
dc.titleConsistance d'un estimateur de minimum de variance étendue
dc.typetext

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