Likelihood-based cross-validation score for selecting the smoothing parameter in maximum penalized likelihood estimation

DOI10.1080/03610929908832379zbMath1069.62525OpenAlexW2045955829MaRDI QIDQ4266878

Shingo Shirahata, Wataru Sakamoto

Publication date: 1999

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610929908832379

zbMATH Keywords

smoothing splineAkaike information criterionlogistic regressionPoisson regressionnonparametric generalized linear models

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Generalized linear models (logistic models) (62J12) General nonlinear regression (62J02)

Cites Work

• Unnamed Item
• Smoothing noisy data with spline functions: Estimating the correct degree of smoothing by the method of generalized cross-validation
• Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
• SIMPLE CALCULATION OF LIKELIHOOD-BASED CROSS-VALIDATION SCORE IN MAXIMUM PENALIZED LIKELIHOOD ESTIMATION OF REGRESSION FUNCTIONS
• Nonparametric Roughness Penalties for Probability Densities

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