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

Jenny Häggström

Computational Statistics & Data Analysis, 2013, vol. 62, issue C, 136-148

Abstract: 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.

Keywords: Bandwidth selection; Semiparametric additive model; Backfitting estimation; Mean squared error; Nonparametric regression (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:62:y:2013:i:c:p:136-148

DOI: 10.1016/j.csda.2013.01.010

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