Fast and Accurate Binary Response Mixed Model Analysis via Expectation Propagation

DOI10.1080/01621459.2019.1665529zbMath1452.62067arXiv1805.08423OpenAlexW2972399911MaRDI QIDQ5146042

John T. Ormerod, J. C. F. Yu, Iain M. Johnstone, Hall, Peter, Matthew P. Wand

Publication date: 22 January 2021

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1805.08423

zbMATH Keywords

maximum likelihoodquasi-Newton methodsmessage passinggeneralized linear mixed modelsKullback-Leibler projectionbest predictionscalable statistical methodology

Mathematics Subject Classification ID

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

Related Items

Fast and accurate estimation of non-nested binomial hierarchical models using variational inference

Uses Software

• S-PLUS
• lme4
• BayesDA
• MEMSS
• dclone
• mlmRev
• PRMLT

Cites Work

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• Small Area Estimation
• Graphical Models, Exponential Families, and Variational Inference
• Mixed-Effects Models in S and S-PLUS
• Expectation Propagation in the Large Data Limit
• On expectation propagation for generalised, linear and mixed models
• Estimability and Likelihood Inference for Generalized Linear Mixed Models Using Data Cloning
• Asymptotic Analysis of Mixed Effects Models
• A Family of Variable-Metric Methods Derived by Variational Means
• A new approach to variable metric algorithms
• The Convergence of a Class of Double-rank Minimization Algorithms 1. General Considerations
• Conditioning of Quasi-Newton Methods for Function Minimization
• A Simplex Method for Function Minimization
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