A non-iterative optimization method for smoothness in penalized spline regression

DOI10.1007/s11222-011-9245-0zbMath1322.62004OpenAlexW2003133972MaRDI QIDQ746232

Hirokazu Yanagihara

Publication date: 16 October 2015

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11222-011-9245-0

zbMATH Keywords

B-splinemultiple smoothing parametersgeneralized ridge regressionMallows' \(C_p\) criterionpenalized least square estimation

Mathematics Subject Classification ID

Related Items (2)

Several least-squares problems related to the Hodrick–Prescott filtering ⋮ Equivalence between adaptive Lasso and generalized ridge estimators in linear regression with orthogonal explanatory variables after optimizing regularization parameters

Uses Software

• Matlab
• fminsearch
• gamsel

Cites Work

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• Some Comments on C P
• The Estimation of Prediction Error
• The elements of statistical learning. Data mining, inference, and prediction

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