The topography of multivariate normal mixtures

dc.creatorRay, Surajit
dc.creatorLindsay, Bruce G.
dc.date2006-02-11
dc.date.accessioned2026-07-07T08:07:31Z
dc.date.available2026-07-07T08:07:31Z
dc.descriptionMultivariate normal mixtures provide a flexible method of fitting high-dimensional data. It is shown that their topography, in the sense of their key features as a density, can be analyzed rigorously in lower dimensions by use of a ridgeline manifold that contains all critical points, as well as the ridges of the density. A plot of the elevations on the ridgeline shows the key features of the mixed density. In addition, by use of the ridgeline, we uncover a function that determines the number of modes of the mixed density when there are two components being mixed. A followup analysis then gives a curvature function that can be used to prove a set of modality theorems.
dc.descriptionPublished at http://dx.doi.org/10.1214/009053605000000417 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/math/0602238
dc.identifierhttp://arxiv.org/abs/math/0602238
dc.identifierAnnals of Statistics 2005, Vol. 33, No. 5, 2042-2065
dc.identifierdoi:10.1214/009053605000000417
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/130961
dc.subjectStatistics Theory
dc.subject62E10, 62H05 (Primary) 62H30 (Secondary)
dc.titleThe topography of multivariate normal mixtures
dc.typetext

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