Bandwidth selection for backfitting estimation of semiparametric additive models: A simulation study

A data-driven bandwidth selection method for backfitting estimation of semiparametric additive models, when the parametric part is of main interest, is proposed. The proposed method is a double smoothing estimator of the mean-squared error of the backfitting estimator of the parametric terms. The performance of the proposed method is evaluated and compared with existing bandwidth selectors by means of a simulation study.

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Year of publication:	2013
Authors:	Häggström, Jenny
Published in:	Computational Statistics & Data Analysis. - Elsevier, ISSN 0167-9473. - Vol. 62.2013, C, p. 136-148
Publisher:	Elsevier
Subject:	Bandwidth selection \| Semiparametric additive model \| Backfitting estimation \| Mean squared error \| Nonparametric regression

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10011056600