Selection of smoothing parameters in \(B\)-spline nonparametric regression models using information criteria

DOI10.1007/BF02523388zbMath1047.62032MaRDI QIDQ1880989

Sadanori Konishi, Seiya Imoto

Publication date: 27 September 2004

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

zbMATH Keywords

information criteriasmoothing parameter selection\(B\)-spline smoothingkyphosislaminectomy

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Generalized linear models (logistic models) (62J12) Monte Carlo methods (65C05)

Related Items (18)

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Uses Software

• FITPACK

Cites Work

• On the use of the predictive likelihood of a Gaussian model
• Smoothing noisy data with spline functions: Estimating the correct degree of smoothing by the method of generalized cross-validation
• A practical guide to splines
• Bootstrap methods: another look at the jackknife
• Bootstrapping log likelihood and EIC, an extension of AIC
• Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
• Smoothing methods in statistics
• Smoothness priors analysis of time series
• Penalized Likelihood for General Semi-Parametric Regression Models
• Regression and time series model selection in small samples
• Further analysis of the data by Akaike's information criterion and the finite corrections
• Smoothing Parameter Selection in Nonparametric Regression Using an Improved Akaike Information Criterion
• Generalised information criteria in model selection
• Nonparametric Roughness Penalties for Probability Densities
• On Information and Sufficiency
• A new look at the statistical model identification
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