Sharp adaptive estimation of the drift function for ergodic diffusions

dc.creatorDalalyan, Arnak
dc.date2006-02-28
dc.date.accessioned2026-07-07T08:07:36Z
dc.date.available2026-07-07T08:07:36Z
dc.descriptionThe global estimation problem of the drift function is considered for a large class of ergodic diffusion processes. The unknown drift $S(\cdot)$ is supposed to belong to a nonparametric class of smooth functions of order $k\geq1$, but the value of $k$ is not known to the statistician. A fully data-driven procedure of estimating the drift function is proposed, using the estimated risk minimization method. The sharp adaptivity of this procedure is proven up to an optimal constant, when the quality of the estimation is measured by the integrated squared error weighted by the square of the invariant density.
dc.descriptionPublished at http://dx.doi.org/10.1214/009053605000000615 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/0602659
dc.identifierhttp://arxiv.org/abs/math/0602659
dc.identifierAnnals of Statistics 2005, Vol. 33, No. 6, 2507-2528
dc.identifierdoi:10.1214/009053605000000615
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/130985
dc.subjectStatistics Theory
dc.subject62M05, 62G07, 62G20 (Primary)
dc.titleSharp adaptive estimation of the drift function for ergodic diffusions
dc.typetext

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