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Bandwidth Selection for Backfitting Estimation of Semiparametric Additive Models: A Simulation Study
Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
2013 (English)In: Computational Statistics & Data Analysis, ISSN 0167-9473, Vol. 62, 136-148 p.Article in journal (Refereed) Published
Abstract [en]

A data-driven bandwidth selection method for backfitting estimation of semiparametric additive models, when the 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.

Place, publisher, year, edition, pages
2013. Vol. 62, 136-148 p.
Keyword [en]
Bandwidth selection, Semiparametric additive model, Backfitting estimation, Mean squared error, Nonparametric regression
National Category
Probability Theory and Statistics
Research subject
URN: urn:nbn:se:umu:diva-64072DOI: 10.1016/j.csda.2013.01.010OAI: diva2:587242
Available from: 2013-01-14 Created: 2013-01-14 Last updated: 2013-04-19Bibliographically approved

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Häggström, Jenny
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