A new algorithm for estimating the effective dimension-reduction subspace

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dc.creatorDalalyan, Arnak
dc.creatorJuditsky, Anatoly
dc.creatorSpokoiny, Vladimir
dc.date2007-01-30
dc.date.accessioned2026-07-07T08:08:39Z
dc.date.available2026-07-07T08:08:39Z
dc.descriptionThe statistical problem of estimating the effective dimension-reduction (EDR) subspace in the multi-index regression model with deterministic design and additive noise is considered. A new procedure for recovering the directions of the EDR subspace is proposed. Under mild assumptions, $\sqrt n$-consistency of the proposed procedure is proved (up to a logarithmic factor) in the case when the structural dimension is not larger than 4. The empirical behavior of the algorithm is studied through numerical simulations.
dc.identifierhttps://arxiv.org/abs/math/0701887
dc.identifierhttp://arxiv.org/abs/math/0701887
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/131338
dc.subjectStatistics Theory
dc.titleA new algorithm for estimating the effective dimension-reduction subspace
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