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An iterative plug-in algorithm for P-Spline regression

Sebastian Letmathe () and Yuanhua Feng ()
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Sebastian Letmathe: Paderborn University
Yuanhua Feng: Paderborn University

No 151, Working Papers CIE from Paderborn University, CIE Center for International Economics

Abstract: This paper proposes a new IPI- (iterative plug-in) rule for optimal smoothing for penalised splines with truncated polynomials. The IPI is based on a closed-form approximation to the optimal smoothing parameter. In contrast to a DPI- (direct plug-in) approach the current algorithm is fully automatic and self-contained. Our proposal is a fixpoint-search procedure and the resulting smoothing parameter is (theoretically) independent of the initial value. Like the DPI, the IPI-rule can be employed as a refining stage in order to improve the quality of other selection methods, e.g. Mallow’s Cp, Cross Validation or Residual Maximum Likelihood. Some numerical features of P-Splines as well as the performance of the IPI-algorithm are examined in detail through a simulation study. Our results reveal that our proposal works very well. Practical relevance of the IPI is illustrated by different data examples.

Keywords: P-Splines; smoothing parameter; iterative plug-in; simulation (search for similar items in EconPapers)
JEL-codes: C14 C51 (search for similar items in EconPapers)
Pages: 34
Date: 2022-09
New Economics Papers: this item is included in nep-ecm
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