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A Bootstrap Local Bandwidth Selector for Additive Models

M.D. Martínez-Miranda, R. Raya-Miranda, W. González-Manteiga and A. González-Carmona
Journal of Computational and Graphical Statistics
Vol. 17, No. 1 (Mar., 2008), pp. 38-55
Stable URL: http://www.jstor.org/stable/27594291
Page Count: 18
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A Bootstrap Local Bandwidth Selector for Additive Models
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Abstract

We propose a bootstrap local bandwidth selector for estimating nonparametric additive models. The selector is derived from a bootstrap approximation of the conditional mean squared error, based on a wild bootstrap resampling scheme applied to the estimated residuals. The selector is computed exactly (without involving Monte Carlo approximations) and in practice can be evaluated for many additive estimation methods, including backfitting (bivariate), marginal integration and mixed methods. We study the consistency of the bootstrap approximation and also carry out an empirical simulation study to explore the performance of the proposed selector in comparison with others. The graphical tool SiZer Map enables us to make meaningful comparisons between local and global selectors.

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