Principle of Duality in Cubic Smoothing Spline

Ruixue Du and Hiroshi Yamada
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Ruixue Du: Graduate School of Social Sciences, Hiroshima University, 1-2-1 Kagamiyama, Higashi-Hiroshima 739-8525, Japan
Hiroshi Yamada: School of Informatics and Data Science, Hiroshima University, 1-2-1 Kagamiyama, Higashi-Hiroshima 739-8525, Japan

Mathematics, 2020, vol. 8, issue 10, 1-19

Abstract: Fitting a cubic smoothing spline is a typical smoothing method. This paper reveals a principle of duality in the penalized least squares regressions relating to the method. We also provide a number of results derived from them, some of which are illustrated by a real data example.

Keywords: cubic smoothing spline; principle of duality; penalized regression; right-inverse matrix; ridge regression (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
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