# Using recursive algorithms for the efficient identification of smoothing spline ANOVA models

@article{Ratto2010UsingRA, title={Using recursive algorithms for the efficient identification of smoothing spline ANOVA models}, author={Marco Ratto and Andrea Pagano}, journal={AStA Advances in Statistical Analysis}, year={2010}, volume={94}, pages={367-388} }

In this paper we present a unified discussion of different approaches to the identification of smoothing spline analysis of variance (ANOVA) models: (i) the “classical” approach (in the line of Wahba in Spline Models for Observational Data, 1990; Gu in Smoothing Spline ANOVA Models, 2002; Storlie et al. in Stat. Sin., 2011) and (ii) the State-Dependent Regression (SDR) approach of Young in Nonlinear Dynamics and Statistics (2001). The latter is a nonparametric approach which is very similar to… Expand

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