Localized regression on principal manifolds
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چکیده
We consider nonparametric dimension reduction techniques for multivariate regression problems in which the variables constituting the predictor space are strongly nonlinearly related. Specifically, the predictor space is approximated via “local” principal manifolds, based on which a kernel regression is carried out.
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تاریخ انتشار 2010