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hal.structure.identifierLaboratoire Paul Painlevé - UMR 8524 [LPP]
dc.contributor.authorHoang, Van Ha
HAL ID: 6792
hal.structure.identifierLaboratoire de Mathématiques d'Orsay [LM-Orsay]
dc.contributor.authorPham Ngoc, Thanh Mai
hal.structure.identifierCEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
dc.contributor.authorRivoirard, Vincent
hal.structure.identifierLaboratoire Paul Painlevé - UMR 8524 [LPP]
dc.contributor.authorTran, Viet Chi
HAL ID: 165
dc.date.accessioned2018-03-09T14:43:58Z
dc.date.available2018-03-09T14:43:58Z
dc.date.issued2017
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/17536
dc.language.isoenen
dc.subjectKernel ruleen
dc.subjectnonparametric estimationen
dc.subjectcell divisionen
dc.subjectdeconvolutionen
dc.subjectGrowth-fragmentationen
dc.subject.ddc519en
dc.titleNonparametric estimation of the fragmentation kernel based on a PDE stationary distribution approximationen
dc.typeDocument de travail / Working paper
dc.description.abstractenWe consider a stochastic individual-based model in continuous time to describe a size-structured population for cell divisions. This model is motivated by the detection of cellular aging in biology. We address here the problem of nonparametric estimation of the kernel ruling the divisions based on the eigenvalue problem related to the asymptotic behavior in large population. This inverse problem involves a multiplicative deconvolution operator. Using Fourier technics we derive a nonparametric estimator whose consistency is studied. The main difficulty comes from the non-standard equations connecting the Fourier transforms of the kernel and the parameters of the model. A numerical study is carried out and we pay special attention to the derivation of bandwidths by using resampling.en
dc.identifier.citationpages29en
dc.relation.ispartofseriestitleCahier de recherche CEREMADE, Université Paris-Dauphineen
dc.identifier.urlsitehttps://hal.archives-ouvertes.fr/hal-01623403en
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.description.ssrncandidatenonen
dc.description.halcandidatenonen
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.date.updated2018-03-09T14:40:29Z
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