Abstract
We consider a multivariate nonparametric regression model with random design. We suppose that the regression function possesses a partially linear structure where parametric and nonparametric components are both unknown. We propose an estimation procedure for the nonparametric component. We establish for this procedure a global oracle inequality (under the L∞-norm). This inequality is used to obtain minimax adaptive results on anisotropic Hölder space.
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