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}
}
  • M. Ratto, A. Pagano
  • Published 1 December 2010
  • Mathematics
  • AStA Advances in Statistical Analysis
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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