Reproducing kernels for spaces of zero mean functions. Application to sensitivity analysis - Archive ouverte HAL
Pré-Publication, Document De Travail Année : 2011

Reproducing kernels for spaces of zero mean functions. Application to sensitivity analysis

Résumé

Given a Reproducing Kernel Hilbert Space (H, h., .i) of real-valued functions and a suitable measure μ over the source space, we decompose H as sum of a subspace of centered functions for μ and its orthogonal in H. This decomposition leads to a special case of ANOVA kernels, for which the functional ANOVA representation of the minimal norm interpolator can be elegantly derived. The proposed kernels appear to be particularly convenient for analyzing the effect of each (group of) variable(s) and computing sensitivity indices without recursivity.

Domaines

Autres [stat.ML]
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Dates et versions

hal-00601472 , version 1 (17-06-2011)
hal-00601472 , version 2 (07-12-2012)

Identifiants

Citer

Nicolas Durrande, David Ginsbourger, Olivier Roustant, Laurent Carraro. Reproducing kernels for spaces of zero mean functions. Application to sensitivity analysis. 2011. ⟨hal-00601472v1⟩
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