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.