Nonlinear regression modeling using regularized local likelihood method

DOI10.1007/BF02915429zbMath1094.62076OpenAlexW1971747511MaRDI QIDQ2495325

Sadanori Konishi, Yoshisuke Nonaka

Publication date: 5 July 2006

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

Full work available at URL: https://doi.org/10.1007/bf02915429

zbMATH Keywords

regularizationmodel selectiongeneralized linear modelsinformation criteriarainfall datalocal maximum likelihood estimates

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Estimation in multivariate analysis (62H12) Generalized linear models (logistic models) (62J12) General nonlinear regression (62J02) Monte Carlo methods (65C05) Statistical aspects of information-theoretic topics (62B10)

Related Items (3)

Optimal tuning parameter estimation in maximum penalized likelihood method ⋮ Nonlinear logistic discrimination via regularized radial basis functions for classifying high-dimensional data ⋮ Minimum average deviance estimation for sufficient dimension reduction

Uses Software

• KernSmooth

Cites Work

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• Local Regression and Likelihood
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• Information and Posterior Probability Criteria for Model Selection in Local Likelihood Estimation
• Local Polynomial Kernel Regression for Generalized Linear Models and Quasi-Likelihood Functions
• On Information and Sufficiency

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