A computationally efficient model selection in the generalized linear mixed model

DOI10.1007/s00180-010-0187-3zbMath1226.62070OpenAlexW2030848711MaRDI QIDQ650697

Takuma Yoshida, Masaru Kanba, Kanta Naito

Publication date: 26 November 2011

Published in: Computational Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00180-010-0187-3

zbMATH Keywords

GICsplinesmodel selectionBLUPsmoothing parameterpenalized quasi likelihood

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Nonparametric estimation (62G05) Generalized linear models (logistic models) (62J12)

Related Items (1)

Modelling bilateral intra-industry trade indexes with panel data: a semiparametric approach

Uses Software

• SemiPar

Cites Work

• Unnamed Item
• Information criteria and statistical modeling.
• Generalised information criteria in model selection
• Semiparametric Regression
• The elements of statistical learning. Data mining, inference, and prediction

This page was built for publication: A computationally efficient model selection in the generalized linear mixed model