Nonlinear regression modeling via regularized radial basis function networks

DOI10.1016/j.jspi.2005.07.014zbMath1152.62039OpenAlexW2076443308MaRDI QIDQ947263

Sadanori Konishi, Seiya Imoto, Tomohiro Ando

Publication date: 29 September 2008

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2005.07.014

zbMATH Keywords

regularizationneural networksradial basis functionsmodel selection criterionbankruptcy in Japanmotor cycle impact datanonlinear logistic model

Mathematics Subject Classification ID

Generalized linear models (logistic models) (62J12) General nonlinear regression (62J02) Monte Carlo methods (65C05) Statistical aspects of information-theoretic topics (62B10)

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Cites Work

• Asymptotic theory for information criteria in model selection -- functional approach
• Regularization Algorithms for Learning That Are Equivalent to Multilayer Networks
• Regression and time series model selection in small samples
• Modified AIC and Cp in multivariate linear regression
• Generalised information criteria in model selection
• On Information and Sufficiency
• A new look at the statistical model identification
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